As a Machine Learning / AI Engineer, you will design, develop, and deploy advanced machine learning solutions that support innovation across products and business functions. You will work across the AI lifecycle-from model development and deployment to monitoring and optimization-while collaborating with cross-functional teams to operationalize AI-powered use cases. You will:
- Design, build, and deploy machine learning models for use cases including classification, forecasting, natural language processing, and generative AI.
- Develop scalable data pipelines and production-grade AI services.
- Collaborate with Product, Engineering, and Data Operations teams to translate business needs into AI solutions.
- Continuously enhance model performance, reliability, scalability, and efficiency.
- Implement model monitoring, governance, and lifecycle management best practices.
- Support the deployment of AI and Agentic AI solutions in enterprise environments.
- Contribute to the adoption of responsible AI and production-ready machine learning standards.
Who are you?
You are a solution-oriented professional who enjoys solving complex problems and building scalable AI-powered applications. You combine strong machine learning expertise with software engineering and collaboration skills to deliver impactful solutions in a fast-paced environment.
Ideally, you bring:
- A bachelor's degree specialized in Machine Learning, Artificial Intelligence, Data Science, or a related field.
- Experience developing and deploying machine learning solutions using Python and SQL.
- Knowledge of modern machine learning frameworks and production deployment practices.
- Experience working with large-scale AI systems, LLM-based applications, APIs, and enterprise integrations.
- Familiarity with Generative AI and Agentic AI solution development.
- Understanding of data engineering concepts and cloud platforms such as Azure, AWS, or GCP.
- Experience applying deep learning and computer vision techniques to practical business challenges.
- Strong communication and collaboration skills with cross-functional stakeholders.
What Do We Offer?
At HERE, we are committed to creating an inclusive and engaging work environment where you can grow and thrive.
- Opportunities to work on cutting-edge AI and data-driven solutions
- A collaborative and diverse global team environment
- Continuous learning, development, and career growth opportunities
- Flexible and hybrid work arrangements that support work-life balance
- A culture that values innovation, inclusion, and impact
HERE Technologies is an equal opportunity employer. All qualified applicants will receive consideration without regard to race, color, religion, gender, gender identity, sexual orientation, age, or disability.
Who are we?
HERE Technologies is a location data and technology platform company. We empower our customers to achieve better outcomes - from helping a city manage its infrastructure or a business optimize its assets to guiding drivers to their destination safely.
At HERE we take it upon ourselves to be the change we wish to see. We create solutions that fuel innovation, provide opportunity and foster inclusion to improve people's lives. If you are inspired by an open world and driven to create positive change, join us. Learn more about us on our YouTube Channel.
About the Team:
You will join a collaborative AI and Machine Learning team focused on delivering scalable, production-ready intelligent solutions that create measurable business impact. The team partners closely with Product, Engineering, and Data Operations teams to transform advanced analytics, machine learning, and generative AI capabilities into real-world applications. We encourage continuous learning, innovation, knowledge sharing, and experimentation while maintaining strong engineering and governance standards.
Skills Required
- Bachelor's degree in Machine Learning, AI, Data Science, or related field
- Experience developing and deploying machine learning solutions using Python
- Experience developing and deploying solutions using SQL
- Knowledge of modern machine learning frameworks and production deployment practices
- Experience with large-scale AI systems, LLM-based applications, APIs, and enterprise integrations
- Understanding of data engineering concepts and cloud platforms (Azure, AWS, or GCP)
- Experience applying deep learning and computer vision techniques
- Familiarity with Generative AI and Agentic AI solution development
- Strong communication and collaboration skills with cross-functional stakeholders
HERE Technologies Compensation & Benefits Highlights
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Healthcare Strength — Medical, dental, and vision coverage is paired with life and disability insurance and an Employee Assistance Program. Core health coverage in the U.S. is often described as solid and high quality.
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Leave & Time Off Breadth — Vacation/PTO, sick leave, paid holidays, paid volunteer time, and a formal sabbatical policy are offered. These programs provide notable breadth beyond standard leave.
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Parental & Family Support — Parental leave is offered and often described as generous, with maternity and paternity options referenced. Family-oriented policies are visible, though specific durations differ by location.
HERE Technologies Insights
What We Do
HERE Technologies is a location data and technology company that created the first digital map over 35 years ago. Today we are the world's leading location platform company with a global footprint across 52 countries. Although our strongest presence is in the automotive industry, we also work with leading companies across a wide range of industries, including transport and logistics, mobility, manufacturing and retail and the public sector.
Why Work With Us
At HERE, we're always excited about discovering people who share our passion for building innovative solutions that make the world easier to navigate. We believe our success is powered by our team's diversity, creativity and collaboration and we're always looking for opportunities to grow it further.
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HERE Technologies Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.

