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Vetted Transformers Professionals
Pre-screened and vetted.
Mid-level AI/ML Engineer specializing in LLM fine-tuning, RAG, and MLOps
Senior AI/ML Engineer specializing in computer vision, NLP, and real-time forecasting
Intern Machine Learning Engineer specializing in LLM systems and recommendation/search
Mid-level AI/ML Engineer specializing in LLMs, RAG, and distributed MLOps
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and scalable GPU inference
Principal Machine Learning Scientist specializing in GenAI, LLMs, and RAG
Mid-level Data Scientist specializing in ML for healthcare and strategy analytics
Mid-level Machine Learning Engineer specializing in generative AI, NLP, and MLOps
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
Bhavani Shekhawat
Engineering Manager specializing in AI/ML platforms and 0→1 product delivery
“Player-coach engineer/lead on a high-scale research integrity platform ("Lighthouse") that flags fraud/manipulation signals across ~3M academic manuscripts per year. Owns architecture decisions (ADRs), implements across Go/Java/React services, and introduced NLP (SciBERT embeddings + human-in-the-loop) to assess out-of-context citations while also handling production incidents with a data-consistency-first approach.”
Nishitha Thummala
Mid-level AI/ML Engineer specializing in LLMs, RAG, and scalable inference
“Backend/retrieval-focused engineer with production experience at Perplexity building a large-scale real-time Q&A system using retrieval-augmented generation, emphasizing low-latency, high-quality answers through ranking, context optimization, and caching. Also has orchestration experience from both product-facing LLM pipelines and large-scale infrastructure workflows at Meta, and has partnered with non-technical stakeholders to align AI trade-offs with business goals.”
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).”
Avinash K
Mid-level Software Engineer specializing in AI/LLM and distributed systems
“Recent internship project at Google Workspace building an LLM-driven Python backend pipeline to extract/enrich NLP features from messy customer web domains and integrate them into a Domain Feature Store for personalization and promotions. Also has hands-on Kubernetes/Docker deployment experience for a Digital Signage SaaS backend with GitHub Actions CI, plus strong streaming-systems knowledge (Kafka exactly-once, schema evolution, Flink scaling) and built an information retrieval system handling 30,000+ cases.”
MARCUS JOHNSON
Senior AI/ML Engineer specializing in Generative AI, NLP, and RAG systems
“ML/NLP engineer focused on production-grade data and search/recommendation systems: built an end-to-end pipeline that connects unstructured customer feedback with product data using TF-IDF/BERT, Spark, and AWS (SageMaker/S3), orchestrated with Airflow and monitored for drift. Also has hands-on experience with entity resolution at scale and improving search relevance via BERT embeddings, FAISS vector search, and domain fine-tuning validated with precision@k and A/B testing.”
kartik kanotra
Mid-level Software Developer specializing in cloud data engineering and MLOps
“Software engineer with strong AWS production experience, including an end-to-end historical backfill system exporting ~10PB of CloudWatch logs into a data lake using Step Functions/Kinesis/Lambda/Firehose/Glue. Emphasizes reliability and operability (DynamoDB checkpointing, monitoring dashboards, CI/CD with canary tests) and has also built customer-facing UI work for the Visa Developer Portal using Angular + Spring Boot, plus React/Redux frontend work.”
Senior Software Engineer specializing in AI/ML evaluation and full-stack systems
Mid-level AI/ML Engineer specializing in LLMs, ranking systems, and MLOps
Mid-level AI Solutions Architect & Product Leader specializing in enterprise GenAI systems
Gowri Kajipuram
Mid-level AI/ML Engineer specializing in LLMs, RAG, and multimodal deep learning
“ML/LLM engineer who has built and productionized a large multimodal LLM pipeline end-to-end—fine-tuning a 20B+ parameter model with distributed/FSDP training and deploying on Kubernetes via Triton for ~5x throughput. Strong focus on reliability and safety (monitoring with SHAP, guardrails, A/B testing) with reported ~22% relevance lift and reduced harmful/incorrect outputs, plus experience orchestrating ETL/retraining workflows with Airflow across S3/Snowflake/RDS.”