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Vetted scikit-learn Professionals
Pre-screened and vetted.
Intern Data Scientist specializing in NLP and Large Language Models
Mid-level AI/ML Data Engineer specializing in analytics, ML pipelines, and LLM applications
Mid-level AI Data Scientist specializing in financial risk, fraud detection, and NLP/LLM systems
Mid-Level Software Engineer specializing in cloud-native distributed systems
Mid-level AI/ML Engineer specializing in MLOps, distributed ML, and RAG pipelines
Mid-level Data Scientist specializing in marketing analytics and scalable data platforms
Senior Data Scientist specializing in Generative AI, NLP, and MLOps
Senior Machine Learning Engineer specializing in NLP, Generative AI, and healthcare/legal AI
VP Data Engineer specializing in AI-driven analytics platforms for investment management
Mid-level Data Engineer specializing in AI/ML data platforms and real-time streaming
Mid-level Data Engineer specializing in cloud lakehouse and streaming pipelines
Executive Engineering Leader specializing in Telehealth Platforms and Healthcare IT
Abhishikth Meesala
Mid-level AI/ML Engineer specializing in NLP, Generative AI, and fraud detection
“At PwC, built and productionized an agentic RAG enterprise search assistant over 6M internal documents (8M embeddings), deployed across AWS and GCP. Drove major retrieval gains (72%→92% precision via BM25+dense hybrid with RRF and cross-encoder re-ranking), reduced hallucinations 30%, achieved <2s latency at 50–60K queries/month, and cut support tickets 30%—boosting adoption to 2,500 users by adding source-cited answers.”
JYOTHI N
Senior Data Scientist specializing in analytics, experimentation, and BI on AWS
“Data/ML practitioner focused on healthcare data quality and record linkage: analyzed 10M+ records, built anomaly detection and NLP-driven entity resolution, and automated AWS ETL/validation pipelines (Glue/Redshift/Lambda), cutting data errors by 40% and generating $500k in annual savings. Has hands-on experience with embeddings (Sentence Transformers/spaCy), FAISS vector search, and fine-tuning for domain-specific matching.”
Longyang Xu
Junior Full-Stack Software Engineer specializing in cloud microservices and ML-driven products
“Backend engineer with hands-on ownership of Python/Flask microservices and recommendation systems across edtech and telecom. Deployed and operated real-time personalization/recommendation platforms on AWS EKS with Jenkins-based CI/CD, GitOps-style declarative configs, and strong observability practices. Has migration experience moving legacy mixed environments to modern containerized Kubernetes and built Kafka pipelines feeding ML services while managing schema evolution.”
Hari Kiran Reddy Rommala
Mid-Level Full-Stack Software Engineer specializing in cloud-native data platforms
“LLM/agentic systems practitioner who specializes in moving customer prototypes into production within microservices environments, emphasizing reliability, latency, security, and measurable success metrics. Experienced in real-time troubleshooting using logs/traces and in enabling adoption through hands-on developer workshops (including live coding in Java Spring Boot) and pre-sales POCs that address technical objections and integration risk.”
Abhyush Rajak
Mid-level Backend Software Engineer specializing in FinTech APIs and microservices
“Backend/event-driven systems engineer who built an end-to-end “software robot” for AI-driven invoice processing: FastAPI ingestion + OCR integration + classification mapping, with strong emphasis on reliability (idempotency, retries) and scalability (background workers, event-driven architecture). Experienced in production-grade distributed systems tooling (Kafka, Docker/Kubernetes, GitHub Actions, ArgoCD) and real-time debugging via tracing/telemetry, and expects $10k–$12k/month.”