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Vetted Hugging Face Professionals

Pre-screened and vetted.

CL

Intern Machine Learning Engineer specializing in LLMs, RAG, and model quantization

San Francisco, California1y exp
DoorDashUCLA
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BC

Principal Data Scientist specializing in ML, NLP, and forecasting for marketing and supply chain

Arlington Hts, IL14y exp
GoogleDePaul University
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FS

Mid-level Data Scientist specializing in ML for healthcare and strategy analytics

New York, NY5y exp
Columbia University Irving Medical CenterUC Berkeley
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BM

Mid-level AI/ML Engineer specializing in LLMs, RAG, and production MLOps

San Francisco, CA6y exp
Scale AISaint Louis University
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SP

Staff Data Scientist / AI-ML Engineer specializing in fraud detection, NLP, and recommendations

Sunnyvale, CA11y exp
WalmartIIEST Shibpur
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DW

Staff Full-Stack Engineer specializing in data engineering and real-time event platforms

Houston, TX10y exp
SalesforceMonash University
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TB

Senior Software Engineer specializing in FinTech payments and scalable platforms

San Francisco, CA10y exp
StripeUniversity of Houston
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BS

Engineering Manager specializing in AI/ML platforms and 0→1 product delivery

Cambridge, MA15y exp
ElsevierHarvard University

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.

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NT

Mid-level AI/ML Engineer specializing in LLMs, RAG, and scalable inference

San Francisco, CA6y exp
PerplexityUniversity of Nebraska Omaha

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.

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KM

Kowshika M

Screened

Mid-level AI/ML Engineer specializing in LLM fine-tuning, inference optimization, and AI safety

Santa Clara, CA5y exp
NVIDIAOregon State University

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.

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KT

Kenil Tanna

Screened

Staff-level Machine Learning Engineer specializing in LLMs and MLOps for Financial Services

New York, NY7y exp
JPMorgan ChaseIIT Guwahati

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).

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HL

Hung-Chih Liu

Screened

Mid-level Distributed Systems & AI Infrastructure Engineer

Sunnyvale, CA3y exp
AmazonUCLA

Backend/full-stack engineer (Amazon experience) who built an AWS-based integration testing platform using Flask, ECS, Docker, and CloudWatch—cutting 1000+ test cases from ~5 hours to ~30 minutes while improving log visibility for non-engineering users. Also led a zero-downtime EU region migration with rigorous ORR testing, and built a Kinesis/Firehose/S3 + Glue/Spark replay mechanism for resilient data recovery. Side project: reproducible, cost-efficient LLM hosting platform on EKS using CDK and Karpenter for scale-to-zero.

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DM

Dinesh Mishra

Screened

Executive AI Product Leader specializing in FinTech and agentic AI platforms

San Francisco, CA19y exp
PayzoMoney.aiVellore Institute of Technology

Fintech/neobank CTO (5+ years across US and UK markets) now building Payzo Money, a fintech copilot for SMBs covering expenses, accounting, invoicing, and payroll. Pre-revenue and seeking a $5M seed round, with active Bay Area conversations and a clear focus on bank sponsorship plus compliance/operations readiness; leverages Claude-based AI agents to accelerate building with limited resources.

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KS

Mid-level AI/ML Engineer specializing in LLMs, RAG, and MLOps

CA, USA4y exp
AnthropicCalifornia State University, Long Beach

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.

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KK

Mid-level Software Developer specializing in cloud data engineering and MLOps

NYC, New York3y exp
AmazonNYU

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.

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OJ

Ollie Jones

Screened

Executive Unity/XR Engineer specializing in real-time mocap and volumetric streaming

8y exp
Trickshot

Technical Director/Unity Lead who has shipped multiple Meta Quest immersive experiences and built custom Unity editor tooling to solve content-heavy pipeline constraints, enabling artists to push content directly into a Unity sandbox. Also prototyped a Unity restaurant simulation where an LLM drives NPC reasoning and state machines, using RAG and memory augmentation to reduce hallucinations and stuck behaviors.

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DS

Entry Software Engineer specializing in AI infrastructure and ML inference systems

Seattle, WA2y exp
AmazonUniversity of Illinois Urbana-Champaign
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KR

Mid-level AI/ML Engineer specializing in NLP/LLMs and production ML systems

Allen, TX4y exp
AnthropicUniversity of North Texas
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PP

Mid-level AI/ML Engineer specializing in LLMs, RAG, and multi-agent systems

Centerton, AR6y exp
MetaUniversity of the Cumberlands
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ZQ

Intern Full-Stack Engineer specializing in AI-driven RAG applications

Menlo Park, CA1y exp
MetaUSC
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NW

Junior ML/NLP Engineer specializing in LLM fine-tuning and evaluation

Stanford, CA2y exp
Openproof CoursewareStanford University
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HP

Mid-level Machine Learning Engineer specializing in LLMs, RAG, and GPU-accelerated cloud systems

Santa Clara, CA4y exp
NVIDIAConcordia University Wisconsin
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AR

Intern Biomedical Data Scientist specializing in healthcare AI and LLM-based clinical NLP

Remote2y exp
Citrus OncologyStanford University
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