Responsibilities

- Design, train, evaluate, and deploy scalable machine learning models and predictive data pipelines.
- Implement automated data preprocessing, feature engineering, and hyperparameter tuning frameworks.
- Deploy low-latency, containerized model inference APIs and microservices using FastAPI, Docker, and Kubernetes.
- Integrate vector search indices and embedding models with enterprise backend systems and SaaS applications.
- Monitor production model performance, latency, data drift, and establish automated continuous training (CT) loops.
- Collaborate with cross-functional software teams to identify high-value AI opportunities across client products.

Skills

- 2 to 5 years of hands-on skilled experience developing and deploying machine learning models in production.
- Strong proficiency in Python and modern ML libraries: NumPy, Pandas, Scikit-Learn, PyTorch, or TensorFlow.
- Working experience with vector databases (Pinecone,



Milvus, Qdrant, Chroma) and semantic similarity search.
- Hands-on experience deploying models on cloud platforms (AWS SageMaker, GCP Vertex AI, or Azure ML).
- Familiarity with MLOps best practices, versioning (MLflow, DVC), and containerization (Docker).
- Strong foundational knowledge of linear algebra, probability, statistics, and neural network architectures.

Qualifications

- B.Tech / B.E. / M.Tech / MCA in Computer Science, Data Science, AI/ML, or related quantitative field.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 AI / Machine Learning Engineer (Sahibzada Ajit Singh Nagar)
🏢 Trigvent Solutions
📍 Sahibzada Ajit Singh Nagar