Job Description
Ovii's Interpretation of the Role
The DS/ML Engineer will design, build, and ship end‑to‑end machine‑learning systems for an AI engineering platform. Responsibilities span evaluation infrastructure, model routing economics, scoring pipelines, and MLOps lifecycle work, requiring strong Python, SQL, and statistical skills.
Role Snapshot
- Build and ship end‑to‑end DS/ML features
- Create evaluation backbones and rubrics
- Design model routing and cost‑quality trade‑offs
- Develop scoring, measurement, and signal quality pipelines
- Collaborate on MLOps lifecycle (versioning, monitoring, drift detection)
- Work across backend, frontend, and data pipelines
Must-Have Requirements
- Python
- SQL
- Applied statistics
- Data Science
- Machine Learning
- Software Engineering
Nice-to-Have Signals
- LLM prompting / API usage
- Evaluation or observability tooling for LLM features
- Information retrieval / entity‑matching / record‑linkage
- Developer‑productivity or code‑analytics experience
- LLM evaluation
- Information retrieval
- Developer productivity
Work Setup
- Location: Bangalore, India
- Work mode: ONSITE
- Employment type: Full-Time
Eligibility Gates
- Visa sponsorship: unknown
Not Specified in JD
- Salary range
- Visa sponsorship
- Remote eligibility
- Education requirement
- Certifications
- Relocation
- Notice period
- Travel
- Security clearance
- Coding test
- Portfolio
- GitHub
- Writing sample
- Cover letter
What You'll Likely Work On
- Build evaluation systems: failure taxonomies, LLM‑as‑judge rubrics, golden datasets, and calibration pipelines
- Design and run model routing experiments balancing cost, quality, and latency
- Turn noisy real‑world signals into trustworthy scores using statistical rigor
- Implement full‑lifecycle MLOps: feature pipelines, model versioning, rollout, and drift monitoring
- Collaborate with engineering to serve models at low latency and maintain production reliability
Good Fit If You Have
- Curiosity about product decisions beyond pure modeling
- Comfort experimenting with LLMs and prompt engineering
- Interest in developer‑productivity or DevEx data
Skills
- Python
- SQL
- Applied statistics
- Large Language Model (LLM) prompting & APIs
- Evaluation & observability tooling
- Information retrieval / entity‑matching
- Developer productivity & code analytics
- MLOps (model versioning, monitoring, drift detection)