AppTestify - MLOps Engineer - Python (4-7 yrs)

ML Engineer (MLOps)

Experience Required : 4-7 Years

Location : Pune, Bangalore, Indore

About the Role :

We are seeking a talented and proactive ML Engineer (MLOps) with 4-7 years of experience to join our growing team. In this hands-on role, you will be instrumental in building, deploying, and maintaining our machine learning production systems. You will contribute to the development of scalable and reliable ML infrastructure, ensuring our models transition smoothly from research to production. If you have a solid background in Python, databases, and core MLOps practices, and are eager to grow your expertise in a dynamic environment, we encourage you to apply!

Key Responsibilities :

- ML System Development Contribution : Contribute to the design, development, and implementation of MLOps pipelines and infrastructure to deploy, monitor, and manage machine learning models in production.

- Code Development & Quality : Write clean, scalable, and well-documented Python code for ML pipelines, APIs, and infrastructure components. Participate actively in pull requests and address issues identified by linters/scanners.

- Collaboration & Support : Work closely with data scientists, researchers, and other engineering teams to understand model requirements and ensure seamless integration into production.

- Scrum & Agile Participation : Actively participate in Agile/Scrum ceremonies, including sprint planning, daily stand-ups, and retrospectives, contributing to efficient project delivery.

- Problem Solving & Scoping : Assist in scoping ML engineering issues and translating requirements into actionable technical tasks.

- Code Review Engagement : Participate in code reviews for team members, providing and receiving constructive feedback.

- Production Support : Support the deployment of ML models to production, monitor their basic performance, and assist in troubleshooting issues.

- Documentation : Create and maintain technical documentation for MLOps pipelines and infrastructure.

Technical Skills & Technology Stack :

- Programming Languages : Strong proficiency in Python for developing ML solutions and infrastructure.

- Databases : Hands-on experience with PostgreSQL or other relational databases for data storage and management.

- Cloud & Storage : Familiarity with cloud storage solutions like Amazon S3 and basic understanding of container orchestration services (e.g., ECS, Docker).

- MLOps Platforms : Experience with MLFlow for experiment tracking, model management, and deployment.

- Version Control : Proficient with GitHub for source code management, pull requests, and collaborative development workflows.

- Machine Learning : Solid understanding of general machine learning concepts and algorithms. Exposure to Large Language Models (LLMs) is a plus.

Required Qualifications :

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

- 4-7 years of progressive experience as an ML Engineer, Software Engineer, or a similar role with a focus on MLOps principles.

- Proven hands-on experience in building and deploying ML models.

- Strong analytical, problem-solving, and debugging skills.

- Good communication and collaboration abilities, with experience working in cross-functional teams.

Preferred Qualifications :

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

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

- Prior experience in a product-driven environment.

Why Join Us?

- Work on exciting ML projects that have a direct impact.

- Opportunity to learn and grow in the MLOps domain.

- Collaborate with experienced engineers and data scientists.

- Engage with cutting-edge ML technologies, including LLMs.