About Company :They balance innovation with an open, friendly culture and the backing of a long-established parent company, known for its ethical reputation. We guide customers from what’s now to what’s next by unlocking the value of their data and applications to solve their digital challenges, achieving outcomes that benefit both business and society.About Client:Our client is a global digital solutions and technology consulting company headquartered in Mumbai, India. The company generates annual revenue of over $4.29 billion (₹35,517 crore), reflecting a 4.4% year-over-year growth in USD terms. It has a workforce of around 86,000 professionals operating in more than 40 countries and serves a global client base of over 700 organizations.Our client operates across several major industry sectors, including Banking, Financial Services & Insurance (BFSI), Technology, Media & Telecommunications (TMT), Healthcare & Life Sciences, and Manufacturing & Consumer. In the past year, the company achieved a net profit of $553.4 million (₹4,584.6 crore), marking a 1.4% increase from the previous year. It also recorded a strong order inflow of $5.6 billion, up 15.7% year-over-year, highlighting growing demand across its service lines.Key focus areas include Digital Transformation, Enterprise AI, Data & Analytics, and Product Engineering—reflecting its strategic commitment to driving innovation and value for clients across industries.JD: Senior Machine Learning EngineerEXP-10+ YrsCore Focus: Python-first ML engineering with strong Infrastructure‑as‑Code (Terraform) and production deployment experience on GCP.Key Responsibilities & SkillsPython & ML EngineeringExpert‑level Python with strong OOP and functional programming skillsHands‑on experience building, testing, and optimizing production‑grade ML codeProficiency with ML/DL libraries: TensorFlow, PyTorch, scikit‑learn, pandas, NumPy, PySparkStrong understanding of end‑to‑end model lifecycle: training, versioning, deployment, and monitoringInfrastructure as Code & AutomationStrong hands‑on experience with Terraform for provisioning and managing GCP infrastructureAutomating ML platforms, pipelines, and environments using IaCExperience with Docker for containerized ML workloadsFamiliarity with Kubernetes (GKE) is a plusCloud & ML Platforms (GCP)Experience using Vertex AI for model training, deployment, and lifecycle managementWorking knowledge of GCP services such as BigQuery, Cloud Storage, Cloud Run, Pub/Sub, Dataproc, and DataflowSolid understanding of GCP IAM and VPC conceptsMLOps & CI/CDBuilding and maintaining ML pipelines using Vertex AI Pipelines, Airflow, or similar toolsCI/CD experience using GitHub, Jenkins, and/or GCP Cloud BuildMonitoring and observability for deployed ML modelsAPI Development & System DesignDesigning and building RESTful APIs using FastAPI or Flask for real‑time inferenceIntegrating ML models into scalable, fault‑tolerant servicesExperience with microservices, distributed systems, and asynchronous processing
Job Title
Machine Learning Engineer