We’re hiring a Machine Learning Engineer to build and deploy scalable ML solutions that deliver measurable business outcomes. You’ll manage cloud infrastructure, automate ML pipelines, and collaborate across teams to support end-to-end ML development. This fast-growing data product company partners with enterprise clients across industries to deliver innovation-driven digital solutions.

What will you be doing?

• Build and maintain cloud-based ML infrastructure (AWS: SageMaker, EC2, S3, Lambda)
• Automate ML pipelines for data ingestion, training, and deployment
• Deploy production ML models for use cases like pricing, operations, and prediction
• Develop NLP and conversational AI tools
• Work with cross-functional teams to deliver end-to-end solutions
• Optimize workflows for performance and cost
• Set up monitoring and failover systems to ensure reliability
• Stay updated on MLOps, ML tools, and cloud practices

Must Haves:

• Bachelor’s or Master’s in Computer Science, ML, or related field
• 3+ years in ML engineering or related software roles
• Proficient with AWS, Python, SQL, and ML frameworks (e.g., TensorFlow, PyTorch)
• Experience with ML orchestration (Airflow, Kubeflow), CI/CD, Docker, Kubernetes
• Strong grasp of data processing tools (Spark, Pandas) and ML deployment best practices

Nice-To Haves:

• Experience in pricing, recommendations, or real-time analytics
• Background in NLP and A/B testing
• Familiarity with streaming data and experimentation tools