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AI / ML Engineer
Bright & Smart HR SolutionsKottayam, IN1 day ago
Job description3-8 years of hands-on experience in Python programming (advanced knowledge of data structures, OOP, multiprocessing, async programming). Strong expertise in machine learning algorithms , model training, and evaluation techniques. Experience with API development (FastAPI, Flask, Django, or similar). Proven experience in real-time model deployment and serving (TensorFlow Serving, TorchServe, MLflow, or custom solutions). Solid understanding of cloud-native deployments (AWS Sagemaker, GCP Vertex AI, Azure ML) and containerization (Docker, Kubernetes). Knowledge of streaming data frameworks (Kafka, Spark Streaming, Flink) is a plus. Familiarity with CI / CD pipelines for ML (GitHub Actions, Jenkins, or similar). Strong grasp of data engineering concepts (data ingestion, transformation, and storage). Experience in monitoring & logging (Prometheus, Grafana, ELK, or equivalent). Experience with Generative AI (LLMs, diffusion models, transformers) . Exposure to GPU optimization and distributed training . Familiarity with feature stores and advanced MLOps frameworks (Kubeflow, TFX, MLflow).
AI / ML Engineer – 3 to 5 yrs
6 to 8 yrs
NP : Immediate to 1 week (official) | Location : Gurgaon
Job Description – AI / ML Engineer
We are seeking a highly skilled AI / ML Engineer with strong expertise in Python programming, API development, and real-time deployment of ML models . The ideal candidate should have experience in designing, building, and optimizing machine learning pipelines and integrating models into production environments. Key Responsibilities
- Design, develop, and optimize machine learning models using Python and popular ML frameworks (TensorFlow, PyTorch, Scikit-learn, etc.).
- Implement end-to-end ML pipelines including data pre-processing, feature engineering, training, evaluation, and deployment.
- Build and manage RESTful APIs / gRPC services to expose ML models for real-time inference.
- Deploy and scale models in production environments (Docker, Kubernetes, cloud platforms such as AWS, GCP, or Azure).
- Ensure high availability, low-latency, and fault-tolerant real-time ML systems.
- Collaborate with data engineers and software teams to integrate ML solutions into existing applications.
- Conduct performance monitoring, optimization, and retraining of models as needed.
- Apply MLOps best practices for CI / CD pipelines, model versioning, and automated deployment workflows.
- Write clean, efficient, and production-grade Python code following software engineering best practices.
Required Skills & Experience
Nice to Have
Note : AI / ML engineer
Python heavy
Live project hands on experience with deployment
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Engineer • Kottayam, IN