Sr. AI engineer

Accountabilities

• Design, build, and maintain scalable machine learning infrastructure on AWS, including training and deployment pipelines using services such as SageMaker
• Develop and deploy ML models for recommendation systems, fraud detection, credit risk, and personalization use cases
• Collaborate with product and engineering teams to rapidly build and iterate on AI-driven MVPs and production features
• Implement monitoring, logging, and alerting systems to ensure model performance, stability, and reliability in production
• Support end-to-end ML lifecycle operations, including debugging, optimization, and production incident resolution
• Enable cross-functional teams to leverage AI/ML capabilities, including generative AI solutions where applicable
• Design and scale ML architectures to support high growth, ensuring efficiency, cost optimization, and robustness
• Mentor engineers, conduct code reviews, and promote best practices in ML engineering and MLOps
• Stay current with advancements in machine learning, AI frameworks, and cloud technologies, driving continuous innovation

Requirements

• Bachelor’s degree in Computer Science, Machine Learning, Statistics, Physics, Engineering, or a related technical field
• 6+ years of experience in machine learning engineering with proven success deploying production-grade ML systems
• Strong expertise in Python; Golang experience is a plus
• Deep understanding of machine learning concepts including recommendation systems, pattern recognition, data mining, or AI systems
• Proven track record of building ML models from concept to production with measurable business impact
• Strong experience with AWS cloud services for ML model deployment and scaling
• Solid knowledge of MLOps practices, including Kubernetes, Docker, and CI/CD pipelines
• Experience with relational databases, SQL, and data warehouse systems
• Familiarity with data processing frameworks such as Spark or Kafka for real-time or large-scale data handling
• Strong experience with observability tools such as Prometheus, Grafana, or CloudWatch for ML systems
• Demonstrated technical leadership, including mentoring and owning end-to-end delivery
• Strong communication skills and ability to thrive in fast-paced, high-ownership environments
• Nice to have: experience building generative AI systems or LLM-based applications

Benefits

• Competitive salary ranging from 50,000 to 120,000 USD annually (gross)
• Fully remote work setup from India
• Opportunity to work on high-impact AI systems in fintech and digital commerce
• Exposure to large-scale production ML systems and advanced cloud-native architectures
• Fast-paced environment with strong ownership and career growth opportunities
• Continuous learning culture with access to modern AI/ML tools and technologies
• Collaborative, high-performance engineering culture focused on innovation and results

How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether?

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