Senior GenAI, Machine Learning Engineer
Ness Digital Engineering
full-time
Posted on:
Location Type: Remote
Location: Romania
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Job Level
About the role
- design, build, and deploy LLM‑powered and ML‑driven systems that operate at production scale.
- work on advanced data engineering pipelines
- develop intelligent models for large‑scale data processing
- contribute to next‑generation AI capabilities that enhance HERE’s global location and mapping products.
- Build and optimize GenAI and LLM‑based solutions including prompt engineering, fine‑tuning, and model evaluation.
- Develop applied machine learning models for large‑scale data processing, classification, enrichment, and automation.
- Design and implement robust Python‑based pipelines using modern ML frameworks (PyTorch, TensorFlow, HuggingFace, etc.).
- Build scalable data engineering workflows , including ingestion, transformation, and feature pipelines.
- Deploy and maintain production ML systems , ensuring reliability, observability, and performance.
- Collaborate with cross‑functional teams to refine requirements, validate model outputs, and integrate ML components into production services.
- Apply best practices for model lifecycle management , including versioning, monitoring, retraining, and cost‑efficient deployment.
- Contribute to engineering standards, code reviews, and continuous improvement initiatives.
Requirements
- Strong expertise in GenAI / LLM engineering including hands on experience with modern LLM frameworks and tooling.
- Proven experience in applied machine learning, including model development, evaluation, and optimization.
- Advanced Python programming skills and deep familiarity with ML libraries and ecosystem tools.
- Solid understanding of data engineering foundations, including ETL pipelines, distributed processing, and data quality.
- Demonstrated experience deploying production ML systems (batch or real time).
- Experience with cloud platforms (AWS preferred) for scalable ML and data workloads.
- Strong understanding of software engineering best practices, version control, CI/CD, and testing.
- Bachelor’s or Master’s degree in Computer Science, Data Engineering, Machine Learning, or related field.
- 5+ years of experience in ML engineering, data engineering, or software engineering with a strong ML focus.
- Ability to write clean, efficient, and maintainable code.
- Strong analytical mindset, problem solving skills, and attention to detail.
- Comfortable working in fast paced, agile environments.
Benefits
- access to trainings and certifications
- bonuses
- aids
- socializing activities
- attractive compensation
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
GenAILLM engineeringapplied machine learningPython programmingML librariesETL pipelinesdata qualitycloud platformsCI/CDmodel lifecycle management
Soft Skills
analytical mindsetproblem solvingattention to detailcollaborationcontinuous improvementclean code writingadaptabilitycommunication
Certifications
Bachelor's degree in Computer ScienceMaster's degree in Computer ScienceBachelor's degree in Data EngineeringMaster's degree in Data EngineeringBachelor's degree in Machine LearningMaster's degree in Machine Learning