We are seeking an experienced Machine Learning Engineer with 8-12 years of experience to join our team in Chennai. The ideal candidate will have a strong background in software development and machine learning, capable of designing and implementing innovative solutions to complex problems. You will work closely with data scientists, software engineers, and business stakeholders to create and optimize machine learning models that enhance our products and services.The role combines technical expertise in machine learning and data engineering with the ability to engage business functions and identify opportunities where ML creates measurable business value. The Machine Learning Engineer builds robust ML pipelines, drives applied research and experimentation, and collaborates closely with product, operations, R&D, finance, and service functions to translate business needs into ML solutions.

Key Responsibilities

Build and maintain ML pipelines, including data ingestion, pre-processing, training, deployment, and monitoring.

Support fine-tuning and optimization of LLMs and other models for ESAB-specific use cases.

Collaborate with IT and Digital Solutions to ensure scalable and secure infrastructure for ML applications.

Lead exploratory workshops with business functions (Product, Operations, R&D, Finance, Services) to identify high-value ML opportunities.

Translate business challenges into structured ML problem statements with clear ROI and feasibility assessments.

Collaborate with solution architects to integrate ML models into business applications and processes.

Act as a thought leader and advocate for ML adoption, raising organizational literacy and best practices.

Key Performance Indicators (KPIs)

Reliable and scalable ML pipelines implemented and maintained.

On-time delivery of ML support for pilot and production AI projects.

At least 23 applied ML projects per year delivering measurable business value.

Positive feedback from business leaders on exploratory workshops and collaboration.

Compliance with IT/DS standards for scalability, governance, and security.

Skills & Qualifications

Master's degree in Computer Science, Data Engineering, or related field.

Hands-on experience with ML frameworks such as TensorFlow, PyTorch, Hugging Face, scikit-learn, XGBoost.

Proficiency in MLOps tools: MLflow or Weights & Biases, Kubeflow, Airflow or Prefect, Docker/Kubernetes, cloud ML platforms (Azure ML, AWS SageMaker, GCP Vertex AI).

Strong data engineering skills: SQL, Spark/Databricks, data warehouses (Snowflake, BigQuery, Redshift), vector databases (Pinecone, Weaviate, Milvus, FAISS).

Experience building APIs (FastAPI, Flask, REST, GraphQL) for ML model integration into business applications.

Proven ability to lead exploratory workshops with business stakeholders and translate needs into ML solutions.

Excellent communication, facilitation, and storytelling skills.

European shift (11.00 am to 9.00 pm)

Flexibility to work on extended hours