MLOps Engineer (5+ Years Experience) - Mumbai

Maharashtra, Mumbai, India

Full Time Mid-level / Intermediate USD 56K - 104K *

WeAssemble

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Posted 1 day ago

We are seeking a skilled and experienced MLOps Engineer to join our team. With 5+ years of experience, you will be responsible for designing, deploying, and maintaining machine learning infrastructure and systems at scale. This role requires a strong technical foundation, an ownership mindset, and a passion for solving complex problems in a fast-paced environment.Key Responsibilities:

Design and implement scalable data pipelines and engineering infrastructure to support machine learning systems.
Transition offline machine learning models into production-ready systems.
Develop and deploy tools and services for machine learning training, inference, and monitoring.
Implement CI/CD pipelines, automation, and software engineering best practices for ML models.
Ensure robust model versioning, audibility, and data security.
Automate the deployment and scaling of machine learning models in production environments.
Monitor and maintain the performance, accuracy, and reliability of deployed models.
Collaborate with data scientists, software engineers, and stakeholders to streamline ML model operations.
Evaluate and integrate new technologies to enhance system performance and maintainability.
Stay updated on industry trends and advancements in MLOps.

Requirements:

Education: Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related field.
Experience:
- 5+ years in MLOps, Data Engineering, or related fields.
- Proficiency with MLOps tools (e.g., MLFlow, Azure Machine Learning).
- Hands-on experience in building end-to-end ML systems and custom cloud integrations using APIs.
- Expertise in Python, cloud platforms (Azure, AWS, GCP), and big data tools (e.g., Databricks, Hadoop).
- Strong understanding of containerization (Docker) and orchestration (Kubernetes).
- Familiarity with CI/CD practices, benchmarking, software testing, and automation.
Skills:
- Strong software engineering background in multi-language systems.
- Ability to translate business needs into technical solutions.
- Exposure to machine learning methodologies and best practices.
- Excellent problem-solving, communication, and organizational skills.
Mindset:
- Ownership and reliability in delivering high-quality work.
- Curiosity and a consultative approach to exploring new tools and methodologies.
- Hunger to raise the bar in building ML systems and embracing new challenges.