Posted:2 months ago|
Platform:
Work from Office
Full Time
Key Responsibilities: Own the inference and delivery of machine learning insights to multiple customers. Manage, monitor, and scale ML systems, ensuring high performance and availability. Oversee model and data orchestration, driving efficiency and reliability through profiling, refactoring, and advanced engineering. Develop and optimize data pipelines to enhance ML model usage and real-time insights. Collaborate with the technical team to scope engineering milestones, provide updates, and address challenges. Implement MLOps best practices, including model monitoring, drift detection, and event-based model retraining. Qualifications & Experience: Bachelors degree in computer science or a related quantitative field. 10+ years of experience in software engineering and software development life cycle (SDLC). 5+ years of experience with PySpark or SQL. 4+ years of experience deploying ML models in cloud environments (Azure, AWS, or Google Cloud) using Python. 3+ years of experience with CI/CD tools for deploying production-ready AI/ML models. Hands-on experience with Databricks, AzureML, Snowflake, or related technologies. Expertise in MLOps, including model monitoring, drift detection, and automated retraining. Strong problem-solving skills and ability to work in fast-paced, cross-functional teams. [If applicable] Employees working remotely must comply with companys Telecommuter Policy. If youre passionate about building scalable AI/ML solutions and leveraging cutting-edge MLOps technologies , we’d love to hear from you! Please reach-out to h1b@infyshine.com
Infyshine Technologies
Upload Resume
Drag or click to upload
Your data is secure with us, protected by advanced encryption.
My Connections Infyshine Technologies
Bengaluru, Hyderabad
22.5 - 30.0 Lacs P.A.
Chennai, Tamil Nadu, India
6.0 - 10.0 Lacs P.A.
Chennai, Tamil Nadu, India
7.0 - 10.0 Lacs P.A.
Bengaluru / Bangalore, Karnataka, India
3.0 - 7.0 Lacs P.A.
Hyderabad / Secunderabad, Telangana, Telangana, India
3.0 - 7.0 Lacs P.A.
Delhi, Delhi, India
3.0 - 7.0 Lacs P.A.
Noida, Uttar Pradesh, India
3.0 - 9.5 Lacs P.A.
Gurgaon / Gurugram, Haryana, India
7.0 - 14.0 Lacs P.A.
Noida, Uttar Pradesh, India
7.0 - 14.0 Lacs P.A.
Patan - Gujarat, Gujrat, India
4.0 - 11.0 Lacs P.A.