Senior AI/ML Engineer

Company Description GFMNOW, a brand of Acuvera Platforms Private Limited, is a team of dedicated IT professionals specializing in delivering innovative technology solutions tailored to drive business success. With expertise in IT services, consulting, and digital transformations, GFMNOW empowers organizations with cutting-edge technology to achieve their goals. Offering services such as cloud solutions, cybersecurity, managed IT services, and software development, the company takes a client-centric approach to optimize IT infrastructure and enhance business operations. With a strong reputation for reliability and innovation, GFMNOW positions itself as a strategic technology partner, helping businesses stay competitive in a rapidly evolving digital world. Engagement Model AI / ML and Critical Services (Primary Focus) • Amazon SageMaker (training, endpoints, pipelines, model registry, feature store) • SageMaker Pipelines for CI/CD of ML workflows • Amazon Bedrock for foundation models and GenAI use cases • Amazon Comprehend, Rekognition, Textract (prebuilt AI services where custom ML isn’t justified) • Understanding of when to use managed AI services vs. custom model development • AWS Lambda for event-driven and lightweight API workloads • Amazon ECS and/or EKS for containerized services and ML inference • AWS App Runner for simplified container-based application deployment • Amazon API Gateway (REST/HTTP APIs, auth, throttling, routing) • Application Load Balancer (ALB) for service routing and scaling • Amazon S3 for data lakes, model artifacts, and unstructured storage • Amazon RDS (PostgreSQL/MySQL) for transactional application data • Amazon DynamoDB for scalable, low-latency application data • Amazon OpenSearch for search, logging, and vector search (RAG use cases) • AWS Glue and Amazon Athena for data processing and analytics Frontend Development & App Delivery (Secondary Focus) • React.js for enterprise-grade web applications • Next.js for server-side rendering (SSR), static site generation (SSG), and performance optimization • Component-driven UI development and collaboration with UX/design systems • State management patterns and data-fetching strategies appropriate for AI-driven applications • Secure authentication and authorization integration (Cognito, Auth0, MSAL, OAuth2, OpenID Connect) • AWS Amplify for frontend hosting, CI/CD, environment management, and seamless backend integration • Amazon CloudFront for global content delivery and low-latency user experiences • Amazon Route 53 for DNS management and traffic routing • Understanding of frontend performance optimization, accessibility, and observability • Experience integrating frontend applications with AI/ML-backed APIs and real-time data services