Senior Machine Learning Engineer with MLOPS
Actively Reviewing the ApplicationsPeople Prime Worldwide
Job Description
About Client :-
Our client is a French multinational information technology (IT) services and consulting company, headquartered in Paris, France. Founded in 1967, It has been a leader in business transformation for over 50 years, leveraging technology to address a wide range of business needs, from strategy and design to managing operations.
The company is committed to unleashing human energy through technology for an inclusive and sustainable future, helping organisations accelerate their transition to a digital and sustainable world.
They provide a variety of services, including consulting, technology, professional, and outsourcing services.
Job Details:-
location: Pune,
Mode Of Work : Hybrid
Notice Period : Immediate Joiners
Experience : 6 - 10 yrs
Type Of Hire : Contract to Hire
JOB DESCRIPTION:
Grade D1, Rate: INR 15K per day
JD: Senior Machine Learning Engineer
Core Focus: Python-first ML engineering with strong Infrastructure‑as‑Code (Terraform) and production deployment experience on GCP.
Key Responsibilities & Skills
Python & ML Engineering
Expert‑level Python with strong OOP and functional programming skills
Hands‑on experience building, testing, and optimizing production‑grade ML code
Proficiency with ML/DL libraries: TensorFlow, PyTorch, scikit‑learn, pandas, NumPy, PySpark
Strong understanding of end‑to‑end model lifecycle: training, versioning, deployment, and monitoring
Infrastructure as Code & Automation
Strong hands‑on experience with Terraform for provisioning and managing GCP infrastructure
Automating ML platforms, pipelines, and environments using IaC
Experience with Docker for containerized ML workloads
Familiarity with Kubernetes (GKE) is a plus
Cloud & ML Platforms (GCP)
Experience using Vertex AI for model training, deployment, and lifecycle management
Working knowledge of GCP services such as BigQuery, Cloud Storage, Cloud Run, Pub/Sub, Dataproc, and Dataflow
Solid understanding of GCP IAM and VPC concepts
MLOps & CI/CD
Building and maintaining ML pipelines using Vertex AI Pipelines, Airflow, or similar tools
CI/CD experience using GitHub, Jenkins, and/or GCP Cloud Build
Monitoring and observability for deployed ML models
API Development & System Design
Designing and building RESTful APIs using FastAPI or Flask for real‑time inference
Integrating ML models into scalable, fault‑tolerant services
Experience with microservices, distributed systems, and asynchronous processing
Required Skills
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