
Job Description
Ovii's Interpretation of the Role
We are looking for a software engineer who will design, build, and deploy production‑grade AI/ML models that drive business outcomes for life‑science customers. The role sits in the AI/ML team, works onsite in Hyderabad, and collaborates closely with product, engineering, and domain experts.
Role Snapshot
- AI/ML engineering
- Production‑grade model development
- Onsite Hyderabad
- Full‑time individual contributor
- 2‑4 years experience
Must-Have Requirements
- Python
- Rust
- Pandas
- NumPy
- SciPy
- OpenCV
- scikit-learn
- TensorFlow
- PyTorch
- LangChain
- LlamaIndex
- Vector DBs
- Neo4j
- ArangoDB
- Kubeflow
- MLflow
- AI/ML engineering
- ML model development
- MLOps platform usage
- Advanced degree in Computer Science, Machine Learning or related field
Nice-to-Have Signals
- Life‑science domain experience
Work Setup
- Location: Hyderabad, India
- Work mode: ONSITE
- Employment type: Full-Time
Eligibility Gates
- Visa sponsorship: unknown
Not Specified in JD
- Salary range
- Visa sponsorship
- Remote eligibility
- Equity
- Bonus
What You'll Likely Work On
- Implement and deploy ML solutions that improve revenue, engagement, and customer satisfaction
- Collaborate with data product managers, software engineers, and domain SMEs to surface AI/ML opportunities
- Build production‑ready models for recommendation, generation, and predictive analytics
- Monitor model performance, conduct feature engineering, and run experiments for continuous improvement
- Stay current with AI/ML research and help shape its adoption in the life‑science industry
Good Fit If You Have
- Strong communication and interpersonal skills
- Interest in life‑science domain challenges
- Ability to work collaboratively in an onsite team environment
Skills
- Python or Rust
- Data‑science libraries (Pandas, NumPy, SciPy, OpenCV)
- ML frameworks (scikit‑learn, TensorFlow, PyTorch)
- GenAI tools (LangChain, LlamaIndex, Vector DBs)
- Graph databases (Neo4j, ArangoDB)
- MLOps platforms (Kubeflow, MLflow)
- Model monitoring & feature engineering
- Software product lifecycle & DevOps