Machine Learning Engineer

2 weeks ago

Chennai, Tamil Nadu, India Newbie Soft Solutions Full time ₹ 12,00,000 - ₹ 24,00,000 per year

Job Title: Machine Learning Engineer

Overview

The Machine Learning Engineer is a hybrid applied scientist and engineer role within the AI R&D team. This position combines deep technical expertise in machine learning, data engineering, and MLOps with strong business engagement skills. The role involves identifying ML-driven opportunities that deliver measurable business value, building robust ML pipelines, conducting applied research, and collaborating closely with cross-functional teams such as Product, Operations, R&D, Finance, and Services.

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).

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