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: 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