Nova AI/ML Data Engineer
Role details
Job location
Tech stack
Job description
The Senior AI/ML Engineer will work closely with cross functional stakeholders across our client's organization to design, build, and maintain robust ML and AI systems that enable data informed decision making and enriching critical workflows. This role spans the full data lifecycle, from pipeline architecture and ETL development to statistical modeling, dashboarding, and predictive analytics, directly contributing to client performance, sustainability goals, and operational safety., * Collaborate with program managers, engineers, and cross-functional teams to define KPIs, streamline reporting processes, and align strategic goals.
- Conduct statistical analyses and machine learning model development for client performance metrics, including PCA and linear regression-based forecasting.
- Build and manage data pipelines using SQL, Python, and ETL tools to ensure the integrity and scalability of data workflows.
- Apply machine learning algorithms for data processing.
- Deploy machine learning models to a robust production environment.
- Perform bespoke agentic implementations, with a focus on GCP tools such as Vertex AI, ADK, Spanner, and BigQuery.
- Design, develop, and maintain end-to-end business intelligence solutions, enabling impactful decision-making across global programs.
- Develop intelligence reports for operational, quarterly, and monthly business reviews, highlighting key insights and driving program improvements.
- Technical documentation of solutions.
Requirements
Do you have experience in Technical solutions implementation?, * 7+ years in data science, analytics, or data engineering.
- Statistical analysis and regression algorithms for forecasting.
- Machine learning expertise, including feature engineering, clustering techniques, classification algorithms.
- MLOps: hands-on experience deploying machine learning or AI agent systems to robust production environments.
- Experience with multi-agent orchestration.
- Experience with LangChain and LangGraph.
- Hands-on experience with RAG, including chunking, embedding, and vectorization techniques.
- Hands-on experience with controlling LLM hallucinations.
- Knowledge of LLM prompting techniques.
- Hands-on with SQL, must be able to write complex queries, not just read them.
- Python for data and ML work, ie. pandas, scikit learn, Pytorch, Tensorflow.
- Built and maintained data pipelines end to end in a production environment.
- Worked in GCP cloud stack (including Vertex AI or Model Garden).
- Created dashboards for business stakeholders, Looker, Tableau, or equivalent.
- Collaborated with non-technical teams to define KPIs and present findings.
- Familiarity with Agile and sprint-based delivery.
- Strong design and development skills with meticulous attention to detail.
- Strong knowledge of database structure systems and data mining.
- Excellent organizational and analytical abilities.
- Good written and verbal communication skills
- Ability to analyze and troubleshoot complex issues.
- Tools used: SQL, Python, BigQuery, GCP, ETL Pipelines, Multi-agent AI, LLM Integration, ML libraries., * Professional experience in API development, including testing methods, security, and performance tracking.
- Experience with database sharding techniques.
- DevOps experience, including CI/CD, Git, Terraform.
- Deep knowledge of GCP cloud stack.