Machine Learning Engineer
First seen by Alion on Sep 30, 2026.
About Exponentia.ai :
Exponentia.ai is a fast-growing AI-first technology services company, partnering with enterprises to shape and accelerate their journey to AI maturity. With a presence across the US, UK, UAE, India, and Singapore, we bring together deep domain knowledge, cloud-scale engineering, and cutting-edge artificial intelligence to help our clients transform into agile, insight-driven organizations.
We are proud partners with global technology leaders such as Databricks, Microsoft, AWS, and Qlik, and have been consistently recognized for innovation, delivery excellence, and trusted advisories.
Awards & Recognitions :
- Innovation Partner of the Year - Databricks, 2024
- Digital Impact Award, UK - 2024 (TMT Sector)
- Rising Star - APJ Databricks Partner Awards 2023
- Qlik's Most Enabled Partner - APAC
With a team of 450+ AI engineers, data scientists, and consultants, we are on a mission to redefine how work is done, by combining human intelligence with AI agents to deliver exponential outcomes. Learn more : www.exponentia.ai
About the Role :
We are looking for a skilled Machine Learning Engineer with 3 - 5 years of experience in building and deploying scalable machine learning solutions on AWS.
The ideal candidate will work closely with Data Scientists and Engineering teams to productionize customer propensity models, automate ML workflows, and ensure reliable, secure, and cost-efficient deployment of machine learning services. This role requires strong expertise in Python, MLOps, AWS services, and ML model lifecycle management.
Key Responsibilities :
Machine Learning Engineering & MLOps :
- Collaborate with Data Scientists to productionize machine learning models, feature engineering pipelines, and evaluation workflows.
- Develop and maintain automated pipelines for data preparation, model training, validation, deployment, and retraining.
- Implement batch and real-time inference solutions using AWS-native services.
- Build and manage CI/CD pipelines, automated testing frameworks, and deployment processes for ML applications.
- Maintain model versioning, experiment tracking, reproducibility, and rollback strategies.
AWS Platform & Deployment :
- Deploy and manage machine learning workloads using AWS services such as SageMaker, S3, Glue, Lambda, CloudWatch, and EventBridge.
- Design scalable and secure ML architectures aligned with business and operational requirements.
- Optimize infrastructure performance, system reliability, and cloud resource utilization.
- Ensure adherence to security, governance, and operational best practices.
Monitoring & Operational Excellence :
- Implement monitoring for model performance, prediction quality, drift detection, latency, and system health.
- Troubleshoot production issues related to pipelines, deployments, dependencies, and infrastructure.
- Maintain technical documentation, deployment guides, and operational procedures.
- Collaborate with platform, engineering, and business teams to ensure successful delivery and support.
Ideal Candidate Profile :
- 3 - 5 years of experience in Machine Learning Engineering, MLOps, or Data Engineering.
- Strong proficiency in Python, SQL, software engineering best practices, testing, and debugging.
- Hands-on experience with scikit-learn, XGBoost, or LightGBM.
- Exposure to TensorFlow or PyTorch is advantageous.
- Experience with AWS machine learning and data services.
- Strong understanding of ML lifecycle management, deployment strategies, and model monitoring.
- Experience building automated pipelines and scalable cloud-based ML systems.
- Ability to collaborate effectively with cross-functional teams and stakeholders.
Preferred Qualifications :
- Bachelor's or Master's degree in Computer Science, Engineering, Data Science, Machine Learning, or a related field.
- Experience deploying propensity, lead-scoring, recommendation, churn, or predictive analytics models.
- Hands-on experience with MLflow and/or Databricks.
- Understanding of model drift, explainability, governance, and Responsible AI practices.
- AWS Machine Learning or AWS Developer Certification preferred.
- Experience working in Agile/Scrum delivery environments.
Why Join Exponentia.ai?
- Innovate with Purpose : Opportunity to create pioneering AI solutions in partnership with leading cloud and data platforms
- Shape the Practice : Build a marquee capability from the ground up with full ownership
- Work with the Best : Collaborate with top-tier talent and learn from industry leaders in AI
- Global Exposure : Be part of a high-growth firm operating across US, UK, UAE, India, and Singapore
- Continuous Growth : Access to certifications, tech events, and partner-led innovation labs
- Inclusive Culture : A supportive and diverse workplace that values learning, initiative, and ownership
Skills
Python, AWS, MLOps, Machine Learning, CI/CD Pipeline, AWS SageMaker, Monitoring Tools, PyTorch, Tensorflow