Senior ML Ops Engineer

Key Skills

Amazon RedShift, Apache Hadoop, AWS, AWS Glue, Azure, Bayesian networks, Data Privacy, Google Cloud Platform (GCP), Grafana, IT Security, Kubernetes-K8s, Lambda, Prometheus, PyTorch, Scikit-learn, Spark-SQL, TensorFlow

Job Description

We are seeking an experienced ML Ops Engineer to join our team. As an ML Ops Engineer, you will play a crucial role in developing and maintaining our machine learning infrastructure and operational workflows. You will work closely with data scientists, software engineers, and DevOps teams to ensure the smooth deployment and operation of machine learning models in production.

Responsibilities:

• Develop and maintain machine learning infrastructure for production environments.
• Collaborate with data scientists and software engineers to ensure models are production-ready.
• Implement CI/CD pipelines and automate model deployment processes.
• Monitor and troubleshoot production systems hosting machine learning models.
• Establish version control and model tracking using tools like MLflow.
• Optimize and scale ML workflows for efficiency and scalability.
• Ensure security and compliance with data privacy regulations.

Requirements:

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• 3 to 5+ years of experience in ML Ops or related roles.
• Strong knowledge of DevOps principles, CI/CD pipelines, and version control systems.
• Experience with AWS Cloud ML services (e.g., Amazon SageMaker, AWS Glue, AWS Lambda).
• Proficiency in Python and ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Familiarity with MLflow or similar model tracking and deployment tools.
• Understanding of Docker, Kubernetes, networking, security, and data privacy.
• Strong problem-solving and communication skills.

Preferred Qualifications:

• Experience with other cloud platforms (e.g., AWS, GCP, Azure).
• Knowledge of data engineering and data warehousing concepts.
• Familiarity with monitoring and logging tools (e.g., ELK stack, Prometheus, Grafana).
• Experience with automated testing frameworks for ML models.
• Knowledge of Big Data technologies (e.g., Apache Spark, Hadoop).

Note: Years of experience required may vary based on the position's level and seniority.

What We Offer

• Consulting environment with a hyper-growth company
• Multi-cultural environment
• An opportunity to solve complex business challenges and problems for large corporations
• International Exposure and Experience.
• Competitive salary and benefits
• Paid holidays and vacations
• Medical OPD & Health Insurance
• Fuel Allowance
• Employee Life Insurance
• GYM/Health Club Fee Reimbursement
• Mobile & Internet Allowance
• Opportunities to make a difference in a highly productive environment