This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Sr. AI Engineer based in India.
You will join a fast-growing, innovation-driven environment where machine learning and AI systems directly power large-scale fintech and commerce experiences. In this role, you will design and deploy advanced ML models that drive personalization, fraud detection, and credit risk intelligence across a high-traffic platform. You will work at the intersection of AI research, software engineering, and production systems, ensuring models are scalable, reliable, and continuously optimized. The environment is highly dynamic, with strong emphasis on experimentation, rapid iteration, and measurable business impact. You will collaborate closely with product, data, and engineering teams to transform complex data into intelligent, production-ready solutions. This role is ideal for an engineer who thrives in end-to-end ownership of ML systems and enjoys solving real-world problems at scale. You will also contribute to shaping MLOps practices and advancing AI capabilities across the organization.
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Sr. AI Engineer based in India.
You will join a fast-growing, innovation-driven environment where machine learning and AI systems directly power large-scale fintech and commerce experiences. In this role, you will design and deploy advanced ML models that drive personalization, fraud detection, and credit risk intelligence across a high-traffic platform. You will work at the intersection of AI research, software engineering, and production systems, ensuring models are scalable, reliable, and continuously optimized. The environment is highly dynamic, with strong emphasis on experimentation, rapid iteration, and measurable business impact. You will collaborate closely with product, data, and engineering teams to transform complex data into intelligent, production-ready solutions. This role is ideal for an engineer who thrives in end-to-end ownership of ML systems and enjoys solving real-world problems at scale. You will also contribute to shaping MLOps practices and advancing AI capabilities across the organization.
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
- 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
- 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