AI ML Engineer (Data Science)

Job Title: AIML Engineer (Data Science)

Locations: ChennaI 5 Days WFO Notice period : Immediate to 30 Days

Skills : Data Science, Python, Model Building, Kafka, AWS Who we are Tiger Analytics is a global leader in AI and analytics, helping Fortune 1000 companies solve their toughest challenges. We offer full-stack AI and analytics services & solutions to empower businesses to achieve real outcomes and value at scale. We are on a mission to push the boundaries of what AI and analytics can do to help enterprises navigate uncertainty and move forward decisively. Our purpose is to provide certainty to shape a better tomorrow. Our team of 4000+ technologists and consultants are based in the US, Canada, the UK, India, Singapore and Australia, working closely with clients across CPG, Retail, Insurance, BFS, Manufacturing, Life Sciences, and Healthcare. Many of our team leaders rank in Top 10 and 40 Under 40 lists, exemplifying our dedication to innovation and excellence. We are a Great Place to Work-Certified™ (2022-24), recognized by analyst firms such as Forrester, Gartner, HFS, Everest, ISG and others. We have been ranked among the ‘Best’ and ‘Fastest Growing’ analytics firms lists by Inc., Financial Times, Economic Times and Analytics India Magazine

Curious about the role? What your typical day would look like? We are looking for a Data Scientist / Machine Learning Engineer with strong experience in machine learning and real-time stream data processing. The ideal candidate will have hands-on expertise in building scalable ML solutions, developing streaming data pipelines, and working with modern cloud-native technologies. This role requires experience working with Kafka-based event streaming platforms, AWS services, and large-scale data processing environments. The candidate will be responsible for designing, developing, deploying, and monitoring machine learning solutions that support business-critical applications.

Key Responsibilities

• Develop, train, evaluate, and deploy machine learning models for predictive analytics and business optimization use cases.
• Design and implement scalable data pipelines for batch and real-time data processing.
• Build streaming data solutions using Kafka and event-driven architectures.
• Develop robust data ingestion, transformation, and feature engineering workflows using Python.
• Work with AWS services including Lambda, EventBridge, S3, Firehose, CloudWatch, and SageMaker to build and deploy ML solutions.
• Build and optimize data workflows using Snowflake and Snowpark.
• Collaborate with cross-functional teams to understand business requirements and translate them into scalable AI/ML solutions.
• Implement CI/CD pipelines for automated testing, deployment, and monitoring of machine learning applications.
• Use Terraform and Infrastructure-as-Code practices to manage cloud infrastructure.
• Monitor model performance, data quality, and pipeline reliability in production environments.
• Apply best practices for MLOps, model governance, and operational excellence.

Required Skills & Experience

• 3–6 years of experience in Data Science, Machine Learning, or AI Engineering.
• Strong proficiency in Python for machine learning and data processing.
• Hands-on experience in machine learning model development and deployment.
• Experience working with Apache Kafka and streaming data processing.
• Strong understanding of feature engineering, model evaluation, and production ML workflows.
• Experience with AWS services including:
• AWS Lambda
• EventBridge
• SageMaker
• S3
• Firehose
• CloudWatch
• Experience working with Snowflake and Snowpark.
• Knowledge of SQL and large-scale data processing.
• Experience building CI/CD pipelines and deployment automation.
• Hands-on experience with Terraform and cloud infrastructure management.
• Strong problem-solving and analytical skills.

You are important to us, let’s stay connected! Every individual comes with a different set of skills and qualities so even if you don’t tick all the boxes for the role today, we urge you to apply as there might be a suitable/unique role for you tomorrow. We are an equal opportunity employer. Our diverse and inclusive culture and values guide us to listen, trust, respect, and encourage people to grow the way they desire.

Note: The designation will be commensurate with expertise and experience. Compensation packages are among the best in the industry. Additional Benefits: Health insurance (self & family), virtual wellness platform, and knowledge communities.