Machine Learning Engineer

🏢 Summary: Full Stack Engineer role focused on building an AI-native assistant that delivers reliable, persistent, goal-oriented workflows. The position covers frontend, backend and AI integrations, including agent planning, tool use, LLM reliability and real-time interactions in a remote-first global team. 🗂️ Requirements: Professional full-stack engineering experience across frontend and backend systems, System design, distributed applications and API architecture knowledge, Experience with LLMs, RAG systems or AI-powered applications, Ability to own features from concept through production deployment, Pragmatic decision-making in ambiguous, fast-moving environments, Cross-functional collaboration with engineering, Machine Learning and product teams 📃 Skills: Next.js, Python, Node.js, PyTorch, OpenAI, Anthropic, LLMs, RAG, SQL, NoSQL, Kubernetes, Docker, APIs 🏢 Description: About the product Our client is developing an AI-native assistant designed to support everyday communication, organization, errands and complex workflows with minimal user input. The product must reliably manage long-running processes, retain context, interact with external tools and complete real-world tasks despite the non-deterministic nature of modern AI models. The company’s objective is to make everyday activities significantly faster and easier for users. About the role We are looking for a Full Stack Engineer specializing in AI systems to build the product layer that transforms advanced AI capabilities into useful, production-grade workflows. You will help design how AI agents plan and operate, interact with external tools, manage failures, recover from errors and deliver consistent value to users. This is an end-to-end engineering role covering frontend development, backend systems and AI integrations. What you will do Build end-to-end product functionality across frontend, backend and AI integrations. Design agent workflows covering planning, tool use, multi-step execution, failure handling and recovery. Integrate LLMs, memory systems and external tools into applications that operate reliably under real-world conditions. Design real-time AI interactions involving streaming, partial results and strict latency requirements. Improve system reliability, observability and fallback mechanisms. Collaborate closely with Machine Learning, backend and product teams to deliver functionality from concept to production. Continuously improve the product based on real-world usage, evaluation results and observed failure modes. What we are looking for Strong professional experience in full stack engineering across frontend and backend systems. Solid understanding of system design, distributed applications and API architecture. Experience working with LLMs, RAG systems or other AI-powered applications. Ability to operate effectively in ambiguous situations and make pragmatic engineering decisions. Strong ownership and the ability to take functionality from an initial idea through implementation and production deployment. Confidence working in a fast-moving environment with evolving product requirements. Ability to collaborate effectively across engineering, Machine Learning and product teams. What success looks like AI-native product features progress beyond basic chat interfaces into persistent, goal-oriented workflows. Agent workflows reliably complete multi-step tasks across external tools and multiple user sessions. AI interactions remain responsive and achieve low latency without compromising output quality. Production systems include robust fallback and recovery mechanisms for LLM and external-tool failures. The reliability and completion rate of AI workflows improve through continuous evaluation, monitoring and iteration. Reusable patterns and abstractions support scalable integration of LLMs, memory and external tools. The resulting product experience feels proactive, consistent and dependable to users. Technology stack Next.js Python Node.js PyTorch OpenAI, Anthropic and open-source LLMs SQL and NoSQL databases Kubernetes Docker Compensation and employment The position is offered under an employment contract. The company does not publish a fixed external salary range. Compensation is assessed individually based on: professional experience and technical capability, scope of responsibility, location and relevant market benchmarks, expected impact on the product and organization. Candidates may share their expected compensation at the beginning of the recruitment process. The compensation package consists of a base salary and equity, with flexibility for exceptional candidates. A company laptop will be provided where required for the role. Remote work and global collaboration The company operates as a remote-first, globally distributed organization. There is no fixed company-wide working schedule and no requirement to follow one specific time zone. Team members are expected to maintain sufficient working-hours overlap with their immediate colleagues to collaborate effectively. The successful candidate will work from Poland and collaborate with frontend, backend, Machine Learning and product specialists located across different regions. Poland-based employees join existing global teams rather than a separate local team. The exact reporting line and hiring manager will be confirmed during the recruitment process. How the team works The company believes that outstanding products are built by small, highly capable and hands-on teams. Decisions are made collaboratively, while individuals are expected to take ownership, bring structure to ambiguous problems and execute independently. The team moves quickly while balancing production quality, experimentation and continuous learning from real user behavior. There is no fixed hiring quota for this position. The company is focused on identifying engineers who meet its technical and ownership standards rather than filling a predetermined number of seats. Recruitment process The standard recruitment process consists of up to four stages: Technical assessment, where relevant to the candidate’s background. HR interview. One or more technical interviews. Founder or leadership interview. Particularly strong candidates may be fast-tracked directly to the technical interview stage based on their experience and previous work. Applications are evaluated by members of the technical team. Interviews may be conducted virtually and, where relevant, onsite. The exact format and interviewers may vary. The company aims to make decisions efficiently and provide candidates with a prompt outcome.

🏢 Summary: Full Stack Engineer role focused on building an AI-native assistant that delivers reliable, persistent, goal-oriented workflows. The position covers frontend, backend and AI integrations, including agent planning, external-tool use, LLM reliability and real-time interactions in a remote-first global team. 🗂️ Requirements: Professional full-stack engineering experience, Frontend and backend systems experience, System design expertise, Distributed applications knowledge, API architecture knowledge, LLM, RAG or AI-powered application experience, Production deployment ownership, Cross-functional collaboration with Engineering, Machine Learning and Product teams 📃 Skills: Next.js, Python, Node.js, PyTorch, OpenAI, Anthropic, LLMs, RAG, SQL, NoSQL, Kubernetes, Docker, APIs 🏢 Description: About the product Our client is developing an AI-native assistant designed to support everyday communication, organization, errands and complex workflows with minimal user input. The product must reliably manage long-running processes, retain context, interact with external tools and complete real-world tasks despite the non-deterministic nature of modern AI models. The company’s objective is to make everyday activities significantly faster and easier for users. About the role We are looking for a Full Stack Engineer specializing in AI systems to build the product layer that transforms advanced AI capabilities into useful, production-grade workflows. You will help design how AI agents plan and operate, interact with external tools, manage failures, recover from errors and deliver consistent value to users. This is an end-to-end engineering role covering frontend development, backend systems and AI integrations. What you will do Build end-to-end product functionality across frontend, backend and AI integrations. Design agent workflows covering planning, tool use, multi-step execution, failure handling and recovery. Integrate LLMs, memory systems and external tools into applications that operate reliably under real-world conditions. Design real-time AI interactions involving streaming, partial results and strict latency requirements. Improve system reliability, observability and fallback mechanisms. Collaborate closely with Machine Learning, backend and product teams to deliver functionality from concept to production. Continuously improve the product based on real-world usage, evaluation results and observed failure modes. What we are looking for Strong professional experience in full stack engineering across frontend and backend systems. Solid understanding of system design, distributed applications and API architecture. Experience working with LLMs, RAG systems or other AI-powered applications. Ability to operate effectively in ambiguous situations and make pragmatic engineering decisions. Strong ownership and the ability to take functionality from an initial idea through implementation and production deployment. Confidence working in a fast-moving environment with evolving product requirements. Ability to collaborate effectively across engineering, Machine Learning and product teams. What success looks like AI-native product features progress beyond basic chat interfaces into persistent, goal-oriented workflows. Agent workflows reliably complete multi-step tasks across external tools and multiple user sessions. AI interactions remain responsive and achieve low latency without compromising output quality. Production systems include robust fallback and recovery mechanisms for LLM and external-tool failures. The reliability and completion rate of AI workflows improve through continuous evaluation, monitoring and iteration. Reusable patterns and abstractions support scalable integration of LLMs, memory and external tools. The resulting product experience feels proactive, consistent and dependable to users. Technology stack Next.js Python Node.js PyTorch OpenAI, Anthropic and open-source LLMs SQL and NoSQL databases Kubernetes Docker Compensation and employment The position is offered under an employment contract. The company does not publish a fixed external salary range. Compensation is assessed individually based on: professional experience and technical capability, scope of responsibility, location and relevant market benchmarks, expected impact on the product and organization. Candidates may share their expected compensation at the beginning of the recruitment process. The compensation package consists of a base salary and equity, with flexibility for exceptional candidates. A company laptop will be provided where required for the role. Remote work and global collaboration The company operates as a remote-first, globally distributed organization. There is no fixed company-wide working schedule and no requirement to follow one specific time zone. Team members are expected to maintain sufficient working-hours overlap with their immediate colleagues to collaborate effectively. The successful candidate will work from Poland and collaborate with frontend, backend, Machine Learning and product specialists located across different regions. Poland-based employees join existing global teams rather than a separate local team. The exact reporting line and hiring manager will be confirmed during the recruitment process. How the team works The company believes that outstanding products are built by small, highly capable and hands-on teams. Decisions are made collaboratively, while individuals are expected to take ownership, bring structure to ambiguous problems and execute independently. The team moves quickly while balancing production quality, experimentation and continuous learning from real user behavior. There is no fixed hiring quota for this position. The company is focused on identifying engineers who meet its technical and ownership standards rather than filling a predetermined number of seats. Recruitment process The standard recruitment process consists of up to four stages: Technical assessment, where relevant to the candidate’s background. HR interview. One or more technical interviews. Founder or leadership interview. Particularly strong candidates may be fast-tracked directly to the technical interview stage based on their experience and previous work. Applications are evaluated by members of the technical team. Interviews may be conducted virtually and, where relevant, onsite. The exact format and interviewers may vary. The company aims to make decisions efficiently and provide candidates with a prompt outcome.

🏢 Summary: Staff Machine Learning Engineer role focused on improving advertising marketplace efficiency through machine learning, analytics, pricing, allocation, and auction optimization. The position leads research, experimentation, and production ML systems for large-scale, low-latency ad serving while shaping ML strategy and mentoring technical teams. 🗂️ Requirements: 10+ years of industry experience in machine learning and data science, Expertise in statistics, machine learning, and optimization, Staff-level experience with large-scale, revenue-critical distributed ML systems, Production ML model development and deployment experience, Feature engineering, model serving, monitoring, and continuous improvement experience, Software engineering proficiency in Python, SQL, and Java or Scala, Strong computer science fundamentals, Cross-functional technical leadership experience 📃 Skills: Python, SQL, Java, Scala, Statistics, Optimization, Experimentation, Monitoring 🏢 Description: Teamwork makes the stream work. Roku is changing how the world watches TV Roku is the #1 TV streaming platform in the U.S., Canada, and Mexico, and we've set our sights on powering every television in the world. Roku pioneered streaming to the TV. Our mission is to be the TV streaming platform that connects the entire TV ecosystem. We connect consumers to the content they love, enable content publishers to build and monetize large audiences, and provide advertisers unique capabilities to engage consumers. From your first day at Roku, you'll make a valuable - and valued - contribution. We're a fast-growing public company where no one is a bystander. We offer you the opportunity to delight millions of TV streamers around the world while gaining meaningful experience across a variety of disciplines. About the Team A highly scalable and highly available real-time advertising platform is crucial for supporting and growing Roku's advertising business. The mission of the Ad Engineering Team is to build this platform. The Ad Serving team designs, builds, deploys, and operates Roku’s Supply-Side, Ad Mediation, and Demand-Side platforms, which sit at the core of Roku’s ad monetization and are critical to the business. We are looking for a staff-level machine learning engineer with deep research and data science expertise to lead marketplace intelligence and demand optimization initiatives. About the Role This role will drive improvements in Roku Exchange efficiency by applying advanced data analytics and machine learning techniques to optimize pricing, allocation, and auction across the marketplace. For New York Only - The estimated annual salary for this position is between $195,000 - $510,000 annually. Compensation packages are based on factors unique to each candidate, including but not limited to skill set, certifications, and specific geographical location. This role is eligible for health insurance, equity awards, life insurance, disability benefits, parental leave, wellness benefits, and paid time off. How will I use AI at Roku? At Roku, we don’t just use AI, we work with it. AI agents and smart tools help power drafts, analysis, and repetitive workflows, while our people bring direction, judgment, and accountability. We’re looking for curious, adaptable builders who can show how they’ve used AI or automation to move faster, raise the bar, and scale their impact. We value your AI skills if you have built fluency across the agentic engineering toolchain — coding harnesses like Claude Code or Cursor, MCP servers, custom skills, or agent frameworks. And you can describe projects where you shipped real work with these tools. You know how to drive an agent, verify its output, and ramp on an unfamiliar codebase with an agent helping you. What You'll Be Doing Translate ambiguous business problems into clear hypotheses, measurable objectives, and actionable strategies Develop advanced ML models and research-driven methodologies to drive product innovation and improve business outcomes Design and run live experiments to prototype improvements and validate their effectiveness Build production-grade ML systems that operate reliably in large-scale, low-latency ad serving environments Partner with cross-functional stakeholders to define, plan, and drive the ML strategy for Ad Serving Provide technical leadership and mentorship in machine learning, experimentation frameworks, and applied research best practices We're Excited If You Have 10+ years of industry experience applying machine learning and data science to solve complex, mission-critical real-world problems Deep expertise in statistics, machine learning, and optimization techniques Perform as a staff+ technologist on complex, revenue-critical, large-scale distributed ML systems Hands-on experience building and deploying ML models in production, including feature engineering, model serving, monitoring, and continuous improvement Solid software engineering skills in languages such as Python, SQL, and Java/Scala Strong CS fundamentals with the ability to translate ideas into clean, efficient code with ease Excellent written and verbal communication and collaboration skills Proven track record of leading cross-functional teams and initiatives Publications in leading peer-reviewed conferences or academic journals are a plus Expertise in advertising is a plus #LI-SSC What's Roku's approach to hybrid working? Roku fosters an inclusive and collaborative environment where teams generally work in the office Monday through Thursday. Fridays are generally flexible for remote work, except for employees whose specific roles or assigned office location require five days' a week attendance. What are some of the benefits? Roku is committed to offering a diverse range of benefits as part of our compensation package to support our employees and their families. Our comprehensive benefits include global access to mental health and financial wellness support and resources. Local benefits include statutory and voluntary benefits which may include healthcare (medical, dental, and vision), life, accident, disability, commuter, and retirement options (401(k)/pension). Employees are supported in taking time off, in accordance with local leave policies and other personal needs to support their evolving work and life needs. It's important to note that not every benefit is available in all locations or for every role. For details specific to your location, please consult with your recruiter. Accommodations Roku welcomes applicants of all backgrounds and provides reasonable accommodations and adjustments in accordance with applicable law. If you require reasonable accommodation at any point in the hiring process, please direct your inquiries to EmployeeRelations@Roku.com . What should I know about Roku's culture? Roku is a great place for people who want to work in a fast-paced environment where everyone is focused on the company's success rather than their own. We try to surround ourselves with people who are great at their jobs, who are easy to work with, and who keep their egos in check. We appreciate a sense of humor. We believe a fewer number of very talented folks can do more for less cost than a larger number of less talented teams. We're independent thinkers with big ideas who act boldly, move fast and accomplish extraordinary things through collaboration and trust. In short, at Roku you'll be part of a company that's changing how the world watches TV. We have a unique culture that we are proud of. We think of ourselves primarily as problem-solvers, which itself is a two-part idea. We come up with the solution, but the solution isn't real until it is built and delivered to the customer. That penchant for action gives us a pragmatic approach to innovation, one that has served us well since 2002. To learn more about Roku, our global footprint, and how we've grown, visit https://www.weareroku.com/factsheet . By providing your information, you acknowledge that you want Roku to contact you about job roles, that you have read Roku's Applicant Privacy Notice , and understand that Roku will use your information as described in that notice. If you do not wish to receive any communications from Roku regarding this role or similar roles in the future, you may unsubscribe at any time by emailing WorkforcePrivacy@Roku.com .

🏢 Summary: Partner Engineer role owning the technical relationship and joint product roadmap between Databricks and Microsoft Azure. The position drives cross-company engineering integrations, resolves dependencies, develops reference architectures, and enables field teams on Azure–Databricks solutions. 🗂️ Requirements: 10+ years in cloud solution architecture, partner engineering, or technical program management, Deep expertise in Microsoft Azure services and architecture patterns, Experience managing strategic technical partnerships with VP/C-level stakeholders, Hands-on ability to prototype integrations, debug complex issues, and validate technical feasibility, Experience with Python, SQL, infrastructure-as-code, and API integrations, Ability to manage complex multi-company engineering initiatives and drive consensus, Deep knowledge of the Databricks platform and Microsoft data/AI ecosystem, Strong technical communication and influence across product, engineering, and partner teams 📃 Skills: Azure, Databricks, Python, SQL, APIs, Infrastructure-as-code 🏢 Description: RDQ427R371 At Databricks , we are passionate about enabling data teams to solve the world’s toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world’s best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to tackle technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. About the Role We're seeking a Partner Engineer to own the technical relationship between Databricks Product/Engineering and Microsoft Azure. You will be the primary technical liaison managing our cross product roadmap, driving engineering integrations, and ensuring Databricks products work seamlessly within the Azure ecosystem. You will work directly with Azure Partner SAs, Product Managers, and engineering teams to align roadmaps, identify integration gaps, and accelerate feature delivery. This role reports to the Director of Partner Engineering and works closely with Databricks Product Management, Engineering, and Field teams. Impact you will have Own the Databricks-Azure product-to-cloud technical roadmap, serving as the primary interface between Databricks Product Management and Azure partner teams to ensure alignment on features, integrations, and co-innovation priorities. Track and drive resolution of cross-company dependencies and blockers, manage joint milestone timing with Azure teams, and own the coordination rhythms (recurring syncs, escalation paths) that keep both sides aligned through delivery. Drive engineering integration work between Databricks and Azure product teams coordinating cross-company technical initiatives from scoping through delivery. Create and maintain technical architecture artifacts showing "better together" integration patterns, holistic architecture diagrams, and reference implementations for Azure + Databricks solutions. Enable field teams with technical guidance on Azure-Databricks integration patterns, working with Solution Architects and Customer Success to accelerate Azure customer wins. What we’re looking for 10+ years of experience in cloud solution architecture, partner engineering, or technical program management roles, with deep expertise in Microsoft Azure services and architecture patterns. Proven experience managing strategic technical partnerships at VP/C-level, with ability to navigate complex multi-company engineering initiatives and drive consensus across organizations. Hands-on technical skills with ability to prototype integrations, debug complex issues, and validate technical feasibility of proposed solutions. Experience with Python, SQL, infrastructure-as-code, and API integration patterns. Demonstrated ability to manage high-stakes partner relationships where strategic interests diverge, including setting boundaries and managing expectations while preserving long-term partnership health. Deep knowledge of Databricks platform and Microsoft data/AI ecosystem Excellent communication and influence skills, with ability to translate technical requirements between Product Management, Engineering, and external partner teams. Preferred Prior experience in Partner Solutions Architect or Alliance Engineering roles at cloud providers (AWS, Azure, GCP) or major ISVs. Background working at or with Microsoft - understanding of Microsoft field organization, partner program structure, and decision-making processes. History of driving product-to-product integrations between major platforms. Familiarity with modern development workflows and AI-assisted development tools (Cursor, Claude Code, Codex). Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here . Zone 1 Pay Range $150,200 — $206,450 USD Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here . Zone 2 Pay Range $150,200 — $206,450 USD About Databricks Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn , X , YouTube , and Instagram . Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here . Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone. Applicant Privacy Notice

🏢 Summary: Lead quality validation for HD map products by defining test strategies and building automation-first frameworks for large-scale geospatial data. The role combines end-to-end testing, data pipelines, and cross-functional collaboration to ensure reliable map releases in real-world conditions. 🗂️ Requirements: Bachelor’s or Master’s degree in Computer Science, Software Engineering, or similar, 7+ years of experience in test engineering, data engineering, or related field, SDLC and agile development practices, End-to-end manual and automated testing, Advanced Python automation and data-validation workflows, SQL and data-pipeline experience, Strong analytical problem-solving and attention to detail, Cross-functional communication skills, Successful pre-employment screening 📃 Skills: Python, SQL, SDLC, Agile, Automation, Testing, Validation, Pipelines 🏢 Description: What's the role? You will take ownership of how we validate and scale the quality of HERE’s HD map products. In this role you work at the intersection of data, automation, and product, shaping how large scale geospatial systems are tested and trusted. You will drive modern testing approaches, build automation first validation frameworks, and partner closely with engineering, data science, and product teams to ensure our maps perform reliably in real world conditions. Define and drive test strategies for HD map products, including content validation and hybrid testing approaches Translate product and data specifications into scalable validation frameworks Design and execute test plans, test cases, and data pipelines for product level validation Build and maintain automation driven testing frameworks for large scale data validation Collaborate with Data Science teams to integrate metric driven and machine learning validation signals Partner with Engineering, Product, and Program teams to align validation with release priorities Analyse results, identify gaps, and drive continuous improvement in testing approaches Contribute to tooling, infrastructure, and automation to increase efficiency and coverage Who are you? You enjoy working in complex environments where data, systems, and product come together. You take ownership, think analytically, and are comfortable navigating ambiguity. You are curious by nature and motivated to continuously learn, especially when it comes to new technologies and geospatial systems. Bachelor’s or Master’s degree in Computer Science, Software Engineering, or similar 7+ years of experience in test engineering, data engineering, or a related field Strong understanding of SDLC and agile development practices Solid experience with end to end testing across manual and automation approaches Advanced Python skills including automation and data validation workflows Experience with SQL and working with data pipelines Strong analytical mindset with attention to detail and problem solving Excellent communication skills and ability to work cross functionally Nice to have: Experience with geospatial data models or HD map products Familiarity with HERE tooling such as Unimap, HDLM Viewer, or Map Creator Exposure to cloud environments and pipeline based systems Experience applying machine learning for validation or anomaly detection ISTQB or similar testing certifications What we offer? Work on the development of high-scale services, managing thousands of data processing pipelines Innovative and modern technologies Truly international team of fantastic & talented people from 60+ countries worldwide, working from strong tech hubs located in Europe, the US, and Asia, along with multiple smaller locations Flexible working hours & a flexible approach to office vs. remote work Medical coverage for you and your family Yearly variable bonus This role is eligible for the Creative Tax Incentive scheme in Poland (KUP – Autorskie Koszty Uzyskania Przychodu) Life at HERE in Poland comes with a competitive total rewards package designed to support your health, wellbeing, and performance. This includes a base salary, a Short-Term Incentive (STI) bonus (percentage based on role), a creative tax advantage for eligible positions, private medical care (including dental), life insurance, a meal allowance, vision reimbursement, a remote work allowance (if applicable), access to MyBenefit and Multisport programs, and various wellbeing initiatives. Paid time off, sick leave, and parental leave are provided in accordance with the Polish Labor Code. As part of HERE Technologies employment process, candidates will be required to successfully complete a pre-employment screening process. This offer and any related claims are subject to the successful completion of a pre-employment screening. This will involve employment, education, and criminal verification if applicable. Who are we? Ever checked in somewhere on social media, tracked an online order, or used navigation while driving? Then you have likely interacted with HERE Technologies. Our platform powers location based services across industries including automotive, logistics, and mobility. We build high quality maps and location services that operate at global scale and support mission critical use cases. Within this team, you will work on the validation and quality of HD maps, ensuring that the data powering advanced navigation and autonomous driving is reliable, scalable, and ready for real world use. Closing As part of HERE Technologies employment process, candidates will be required to successfully complete a pre employment screening process. This offer and any related claims are subject to the successful completion of a pre employment screening. This will involve employment, education, and criminal verification if applicable. HERE is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, age, gender identity, sexual orientation, marital status, parental status, religion, sex, national origin, disability, veteran status, and other legally protected characteristics. #LI-TW2  #LI-HYBRID Apply for this job online Email this job to a friend Share on your newsfeed