ML Ops Engineer

Minimum 5 years of relevant experience. Proven experience in machine learning engineering and operations.

Provide hands-on technology expertise

Ownership of all deliverables, timelines, and quality

Co-own the product roadmap

Help support & optimize BAU processes

Profound understanding of machine learning concepts, model lifecycle management, and experience in model management capabilities including model definitions, performance management and integration.

Execution of model deployment, monitoring, profiling, governance and analysis initiatives.

Excellent interpersonal, oral, and written communication; Ability to relate ideas and concepts to others; write reports, business correspondence, project plans and procedure documents.

Solid Python, ML frameworks (e.g., TensorFlow, PyTorch), data modeling, and programming skills.

Experience and strong understanding of cloud architecture and design (AWS, Azure, GCP).

Experience using modern approaches to automating machine learning pipelines.

Agile and Waterfall methodologies.

Ability to work independently and manage multiple task assignments within a structured implementation methodology.

Personally invested in continuous improvement and innovation.

Motivated, self-directed individual that works well with minimal supervision.

Must have experience working across multiple teams/technologies.

Preferred but not essential: Experience with business intelligence tools (preferably PowerBI).

Preferred but not essential: Experience with MLOps tools (e.g., MLflow, Kubeflow).

Ability to commute/relocate:

• Perungudi, Chennai, Tamil Nadu: Reliably commute or planning to relocate before starting work (Preferred)

Application Question(s):

• What is your current CTC?
• What is your expected CTC?
• How quick you can join us?

Education:

• Bachelor's (Preferred)

Experience:

• ML model lifecycle: 5 years (Preferred)
• Python: 5 years (Preferred)
• Azure: 5 years (Preferred)
• AWS: 5 years (Preferred)

Location:

• Perungudi, Chennai, Tamil Nadu (Preferred)

Work Location: In person