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Vetted Keras Professionals
Pre-screened and vetted.
Junior Software Engineer specializing in AWS cloud infrastructure and ML systems
Senior Full-Stack Engineer specializing in cloud-native SaaS and AI/ML integration
Senior AI/ML Engineer specializing in Generative AI and LLM applications
Senior Data & ML Engineer specializing in big data platforms and marketing/ads ML
Senior Data Scientist specializing in AI/Deep Learning and applied machine learning
Mid-level AI/ML Engineer specializing in LLM RAG pipelines and cloud MLOps
Mid-level AI/ML Engineer specializing in GenAI agents and production ML systems
Mid-level Machine Learning Engineer specializing in MLOps and Generative AI
Mid-level Data Scientist/ML Engineer specializing in LLMs, NLP, and recommender systems
Mid-level Agentic AI & ML Engineer specializing in LLM agents and RAG systems
Mid-level Data Scientist specializing in GenAI, LLMs, and MLOps
Junior Data Scientist & Data Engineer specializing in ML and scalable data pipelines
Executive Engineering Leader specializing in E-commerce, SaaS, and EdTech platforms
Deekshit Myakala
Mid-level Software Engineer specializing in cloud automation and data/ETL platforms
“Backend engineer with AWS multi-region production experience building APIs and workflow automation for data center/storage hardware operations (firmware orchestration, maintenance checks, ticketing, dashboards). Also shipped an internal AI chat tool that parses hardware runbooks and incorporates user feedback to retrain the model, and has a strong testing/quality discipline (95%+ coverage) plus database performance tuning via indexing and query monitoring.”
Siddhik Reddy Kurapati
Junior Controls & Motion Planning Engineer specializing in MPC, RL, and autonomous systems
“Robotics researcher focused on learning-based navigation: builds sub-goal generation and cost-to-go models (Bayesian network-based) integrated with motion planning and MPC/NMPC control. Has hands-on ROS 2 package development across vehicles, drones, and manipulators, and uses a broad simulation stack (Isaac Sim, Gazebo, MuJoCo, PyBullet, PX4) to test and integrate systems.”
Asrith Velireddy
Mid-level AI/ML Engineer specializing in MLOps, LLMs, and scalable ML systems
“ML/LLM engineer at Adobe who deployed a transformer-based personalization and campaign-targeting recommender system end-to-end, including PySpark/Airflow pipelines processing 12M+ events/day and containerized inference on AWS SageMaker (Docker/Kubernetes). Also has hands-on LLM workflow experience (RAG, semantic search, prompt optimization, hallucination mitigation) with a metrics-driven approach to reliability, drift monitoring, and reproducible retraining via MLflow.”
Yashshree Patil
Mid-Level Software Development Engineer specializing in full-stack systems and ML
“AWS engineer who productionized an internal ML-driven data pipeline from a notebook prototype into a scalable, observable Python service (schema validation, deduplication, idempotency, safe retries, versioned transforms, CloudWatch alarms), reducing manual effort and improving data accuracy/trust. Experienced diagnosing workflow issues in real time (e.g., upstream schema changes) and partnering with account managers/support to unblock adoption of seller-facing Marketplace features by demonstrating reliability with concrete metrics.”
Kella Dhanush Venkata Sai
Junior ML Engineer specializing in Generative AI and LLM applications
“Built a production internal knowledge assistant using a RAG pipeline over large spreadsheets, PDFs, and support documents, using transformer embeddings stored in FAISS. Focused on real-world production challenges—format normalization, retrieval quality, hallucination reduction (context-only + citations), and latency—using hybrid retrieval, quantization, and containerized deployment, and communicated the workflow to non-technical stakeholders using simple analogies.”