AppTestify - Senior MLOps Engineer - Python (8-15 yrs)

Senior ML Engineer (MLOps)

Experience Required : 8-15 Years

Location : Pune, Bangalore, Indore

About the Role :

We are actively seeking a highly skilled and experienced Senior ML Engineer (MLOps) with 7-10 years of expertise to join our team. In this pivotal role, you will be a lead contributor in architecting, developing, and optimizing our machine learning production systems. You will drive initiatives to ensure our ML models are deployed reliably, scalably, and efficiently, from experimentation to continuous monitoring in production. If you are a hands-on engineer with a proven track record in MLOps, deep expertise in Python, databases, and modern ML tools, and a strong capability to mentor, we invite you to apply!

Key Responsibilities :

- Lead ML System Development : Lead the design, development, and implementation of robust, scalable, and automated MLOps pipelines and infrastructure to deploy, monitor, and manage machine learning models in production environments.

- Code Excellence & Best Practices : Write and enforce standards for clean, scalable, and well-documented Python code for ML pipelines, APIs, and infrastructure components. Ensure rigorous code quality through comprehensive pull requests and efficient resolution of issues found by linters/scanners.

- Technical Guidance & Mentorship : Provide technical guidance and mentorship to junior and mid-level ML engineers, fostering their growth and ensuring adherence to coding standards and best practices.

- Scrum & Agile Leadership : Actively participate in and drive Agile/Scrum ceremonies, contributing significantly to sprint planning, backlog refinement, daily stand-ups, and retrospectives to ensure efficient project delivery.

- Complex Scoping & Solution Design : Take the lead in scoping complex ML engineering issues, translating intricate business requirements into detailed technical specifications, and designing highly robust and scalable MLOps solutions.

- Code Review & Architectural Collaboration : Conduct thorough code reviews for team members, providing constructive feedback and ensuring adherence to architectural patterns, security standards, and performance optimization. Collaborate closely with data scientists, researchers, and other engineering teams on technical strategy and integration.

- Production System Ownership : Oversee the end-to-end deployment of ML models to production, establish comprehensive monitoring, and lead the troubleshooting and resolution of complex production incidents.

- Performance Optimization & Innovation : Proactively identify and implement opportunities for system performance improvement, cost optimization, and the adoption of new MLOps technologies and tools.

Technical Skills & Technology Stack :

- Programming Languages : Expert-level proficiency in Python for developing scalable ML solutions and MLOps infrastructure.

- Databases : Strong hands-on experience with PostgreSQL or other relational databases (e.g., MySQL, NoSQL) for data storage, management, and optimization.

- Cloud & Storage : Proficient with cloud storage solutions like Amazon S3 and advanced understanding/experience with container orchestration services such as ECS (Elastic Container Service), Kubernetes, or other cloud compute services.

- MLOps Platforms : Extensive experience with MLFlow for experiment tracking, model management, deployment, and pipeline orchestration.

- Version Control : Expert-level proficiency with GitHub for source code management, complex pull request workflows, and collaborative development.

- Machine Learning : Solid understanding of Large Language Models (LLMs) and their unique deployment, serving, and monitoring considerations. Strong grasp of general machine learning concepts, model training, evaluation, and serving patterns.

Required Qualifications :

- Bachelor's or Master's degree in Computer Science, Engineering, or a related quantitative field.

- 7-10 years of progressive experience as an ML Engineer, DevOps Engineer, or a similar role with a strong focus on MLOps and production-grade ML systems.

- Proven track record of designing, implementing, and optimizing scalable ML production systems in a lead or senior capacity.

- Demonstrated experience in technical leadership, leading small to medium-sized projects, and mentoring junior engineers.

- Exceptional analytical, complex problem-solving, and debugging skills.

- Excellent communication and collaboration abilities, with extensive experience working effectively in cross-functional teams and presenting technical solutions.

Preferred Qualifications :

- Experience with other MLOps tools (e.g., Kubeflow, Airflow, Vertex AI, SageMaker, Azure ML).

- Familiarity with other major cloud platforms (e.g., Azure, GCP) beyond AWS.

- Contributions to open-source projects related to MLOps or ML infrastructure.

- Experience with streaming data processing (e.g., Kafka, Kinesis).

Location : Pune, Bangalore, Indore

Why Join Us ?

- Lead critical MLOps initiatives that directly impact product success and business outcomes.

- Work with cutting-edge ML technologies, including large-scale LLM deployments.

- Collaborate with a brilliant team of engineers and data scientists in a high-impact environment.

- Significant opportunities for continuous learning, professional growth, and shaping the future of MLOps