Machine Learning Engineer (Lead)

Job Title: Machine Learning Engineer

Overview

Machine Learning Engineer

Key Responsibilities

• Build and maintain

  end-to-end ML pipelines

  , including data ingestion, preprocessing, training, deployment, and monitoring.
• Support

  fine-tuning and optimization of LLMs

  and other models for organization-specific use cases.
• Collaborate with

  IT and Digital Solutions

  to ensure scalable, secure, and compliant ML infrastructure.
• Lead

  exploratory workshops

  across business functions to identify high-value ML opportunities.
• Translate business challenges into

  structured ML problem statements

  with ROI and feasibility analysis.
• Work with

  solution architects

  to integrate ML models into business workflows and systems.
• Act as an

  advocate and thought leader

  for ML adoption, promoting best practices and organizational literacy.

Key Performance Indicators (KPIs)

• Reliable and scalable ML pipelines deployed and maintained.
  
• Timely delivery of ML contributions for pilot and production AI projects.
  
• Completion of

  23 high-impact ML projects per year

  delivering measurable business value.
• Positive feedback from business stakeholders and leadership.
  
• Compliance with IT/DS guidelines for scalability, governance, and security.
  

Skills & Qualifications

Education

• Master’s degree in

  Computer Science

  ,

  Data Engineering

  , or related field.

Technical Skills

• Hands-on experience with:

  TensorFlow, PyTorch, Hugging Face, scikit-learn, XGBoost

  .
• MLOps proficiency:

  MLflow / W&B

  ,

  Kubeflow

  ,

  Airflow / Prefect

  ,

  Docker/Kubernetes

  , cloud platforms (

  Azure ML, AWS SageMaker, GCP Vertex AI

  ).
• Strong data engineering expertise:
  
• SQL, Spark/Databricks
  
• Data warehouses (Snowflake, BigQuery, Redshift)
  
• Vector DBs (Pinecone, Weaviate, Milvus, FAISS)
  
• Experience building APIs for ML model integration (

  FastAPI, Flask, REST, GraphQL

  ).

Business & Soft Skills

• Proven capability to lead

  exploratory workshops

  with business teams.
• Excellent communication, facilitation, and

  technical storytelling

  skills.
• Ability to translate business needs into actionable ML solutions.
  

Reporting Line

• Reports to:

  AI R&D Leader

• Works closely with solution architects, automation engineers, external consultants, and business stakeholders.
  

Additional Submission Note (Important)

Kindly share the below information while submitting profiles:

• Minimum 9+ years of experience

  with a strong background in Machine Learning.

• Number of end-to-end ML model implementations / deployments

  completed in production.

• Experience working with global, multi-cultural stakeholders

  , including distributed teams (US, Europe, APAC).