MLE Senior Engineer

Location: Chennai (Priority)/ Bengaluru / Hyderabad (Work from client location)

Experience: 5 – 10 years

Role Overview:

We are seeking a skilled MLE to join our team. This position is an opportunity for an experienced, MLOPs developer to architect and execute technology projects across multiple client AI and Engineering engagements. S/He will be accountable for building a trusted relationship, at middle and senior management across lines.

Location: Bangalore /Chennai/Hyderabad

Technical Skillset: ML Lifecycle, MLOPs, Python, SQL, Pyspark, Airflow, Jenkins, Docker, GitLab, CI/CD, GCP Services: Data Proc, Cloud Run, BigQuery, Vertex AI, Cloud Storage, Cloud SQL.

Technical Leadership:

As the MLops leader, S/he will support client projects, lead solution design, and contribute to the overall MLOps engineering using cloud-based GCP architectures

Act as a subject matter expert in machine-learning model deployment and MLops pipelines – strong understanding of Machine-learning model building lifecycle, deployment, monitoring and production

Research and evangelize the use of data-science and engineering solutions for strategic decision-making

Articulate business value and advantages of the technological solution to senior business and technology partners

Research, design and implement leading-edge MLops architecture patterns to solve hard problems for the clients and enhance the existing system and identify gaps to onboard new architecture and design.

Bring data-science & engineering thinking to win large AI led digital transformation deals

Responsibilities:

Implement AI and engineering processes and governance methods to manage the risk of delivery





Lead delivery and development teams to ensure architecture is implemented to meet current business needs and future vision

Ability to solve complex challenges/problems and rapidly deliver innovative solutions

Team handling, problem solving, project management and communication skills & creative thinking

Responsible for deployment of new and refreshed models.

Perform pre-deployment validation checks to ensure model output are as expected.

Perform unit testing of the new model pipeline design and automate the deployment process.

Operate and maintain existing applications by supporting the model orchestration pipelines with development, debugging & historical runs.

Working knowledge in developing and automation of CI/CD pipeline, Argo workflows on Python ML app and productionizing the pipeline is good to have.

Thought Leadership:

Lead and energize the teams and clients by providing thought leadership in enterprise-grade machine-learning operations and modern cloud adoption patterns

Act as a Trusted Advisor and build trust with customers through strategic thought, exceptional execution, and technical depth and expertise to help them execute large scale data science/ML projects

Must have Skills: Primary

Be able to collaborate with the DS team for model deployment.





Strong hands-on experience in python coding, pyspark and SQL.

Has working experience in GCP Airflow, to deploy/host models in data proc cluster and run inference on batch data stored in BQ.

Knows how to create DAG’s using different types of operators available.

Good understanding of version control system.

Experience in batch model deployment.

Able to automate repetitive tasks and ensure seamless deployment with minimal manual intervention.

Good written and verbal communication.

Good understanding of end-to-end ML life cycle.

Hands on experience on Google cloud- BigQuery, Dataproc

Strong working experience in Python and PySpark to build production ready ML applications.

Good in identifying the production issues with ML models and pipelines and collaborate with Data Scientists for resolution.

Understanding on the ML terminology and its role in optimizing the model.

Onboard the models for performance and stability metrics to display them in Dashboard UI.

Knowledge of ML services and deployment strategies on GCP and AWS.

Produce build and deployment automation scripts to integrate between services

Good Understanding of Version control system (Gitlab) and working around it.

Experience in working with Batch Model pipelines.

Must have experience in – GCP Services – Cloud Run, BigQuery, Vertex AI, Cloud Storage, Cloud SQL

Collaborate with DS and DE to get the data issues solved.

Good Written and Verbal Communication Skills.

Pay: ₹1,500,000.00 - ₹3,000,000.00 per year

Benefits:

- Paid sick time
- Paid time off
- Provident Fund

Work Location: Hybrid remote in Chennai, Tamil Nadu

📌 MLOps Engineer (India)
🏢 Collabrah Tech Solutions
📍 India