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Vetted Keras Professionals
Pre-screened and vetted.
Mid-level AI/ML Engineer specializing in LLM fine-tuning, RAG, and MLOps
Principal Data Scientist specializing in AI and quantitative investment strategies
Senior Software Engineer specializing in cloud platforms for healthcare and e-commerce
Mid-level Machine Learning Engineer specializing in real-time recommender systems and MLOps
Senior Software Engineer specializing in cloud platforms, data pipelines, and ML
Parth Vadera
Senior AI/ML Data Scientist specializing in recommender systems, LLMs, and MLOps
“ML/NLP leader with 12+ years of impact across LinkedIn, TikTok, and Levi's, building and productionizing multimodal recommendation and embedding-based search systems. Deep experience in entity resolution, vector retrieval, and rigorous evaluation, with cloud-native deployment/monitoring (MLflow, Airflow, SageMaker/Lambda, Azure ML, Kubernetes) and demonstrated double-digit relevance gains at millions-of-users scale.”
Mid-level AI/ML Engineer specializing in LLMs, RAG, and distributed MLOps
Mid-level Software Engineer specializing in distributed systems and big data
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and scalable GPU inference
Principal Machine Learning Scientist specializing in GenAI, LLMs, and RAG
Staff Data Scientist / AI-ML Engineer specializing in fraud detection, NLP, and recommendations
Senior Full-Stack Engineer specializing in cloud, real-time data, and web platforms
Senior Software Engineer specializing in cloud platforms, healthcare imaging, and scalable APIs
Senior Full-Stack Software Engineer specializing in Telehealth and FinTech
Mid-level Software Engineer specializing in Python, distributed systems, and AI backend services
Mid-level AI/ML Engineer specializing in LLM training, RAG, and low-latency inference
Senior Machine Learning Engineer specializing in GenAI, NLP, and recommendation systems
Kowshika M
Mid-level AI/ML Engineer specializing in LLM fine-tuning, inference optimization, and AI safety
“AI/LLM engineer with production experience at NVIDIA, where they fine-tuned and deployed a financial-services chatbot and cut latency ~50% using TensorRT + NVIDIA Triton, scaling via Docker/Kubernetes. Also has consulting experience at Accenture delivering a predictive maintenance solution for a logistics network, bridging non-technical stakeholders with actionable dashboards.”
Kenil Tanna
Staff-level Machine Learning Engineer specializing in LLMs and MLOps for Financial Services
“Machine learning/NLP practitioner at J.P. Morgan who led development of a production RAG system and an entity resolution pipeline for complex financial data. Deep hands-on experience with embeddings (Sentence-BERT), vector search (FAISS/pgvector), LLM fine-tuning (LoRA/PEFT), and rigorous evaluation (human-in-the-loop + A/B testing) backed by strong MLOps on AWS (Docker/Kubernetes, MLflow, Prometheus/Datadog).”
Krishna Sahith Poruri
Mid-level AI/ML Engineer specializing in LLMs, RAG, and MLOps
“ML/LLM engineer who built a production RAG system (GPT-4 + FAISS + FastAPI) to deliver fast, grounded answers from proprietary documents, optimizing for sub-200ms latency and high-concurrency scale. Strong MLOps/observability background: drift monitoring with Prometheus + Streamlit, automated retraining via Airflow, Kubernetes autoscaling, and MLflow-managed model lifecycle, plus inference cost reduction through quantization and structured pruning.”