Data Science ML/Gen AI Engineer (Mid-Level)- Orbit
Irth (company site, opens in a new tab)3–6 yrsRemoteDirect career pageEst. 12–22 LPA
Posted on 9 Sept
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Job description
Structured overview of role & requirements
About This Role
- Develop and productionize machine learning and Generative AI solutions across data lifecycle using Databricks Lakehouse architecture.
- Build and maintain reliable, governed data pipelines with strong data quality, lineage (95% coverage), security, and compliance following defined SLOs (pipeline success 99.5%, MTTD 5min, MTTR 60min).
- Optimize and automate ML/data workflows including CI/CD, monitoring, cost efficiency, and integration of semantic data layers for consistent business metrics.
Minimum Requirements
- 3–6 years of experience in Data Science, Machine Learning, or ML Engineering with production deployment of models.
- Proficiency in Python, SQL, Spark/PySpark and hands-on experience with Databricks ecosystem (Delta Lake, Unity Catalog, Jobs, Medallion architecture).
- Experience with GenAI/LLM including prompt engineering, RAG, vector databases, and related operational considerations.
- Strong knowledge of data governance, security (PII handling, RBAC/ABAC), compliance frameworks (SOC 2, ISO 27001, GDPR) and policy-as-code implementations.
Ideal Candidate Profile
- Comfortable working end-to-end across data engineering, ML development, MLOps, data governance, and cloud platforms, with a focus on production reliability and measurable business impact.
- Experience collaborating cross-functionally with Product, Engineering, and domain teams to define KPIs, design A/B tests, and deliver customer-facing AI/data products.
- Proven ability to build scalable, cost-optimized data and ML infrastructure with strong emphasis on security, compliance, and operational excellence.