

Sully.ai
Senior ML/NLP Engineer (Contract)
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior ML/NLP Engineer (Contract) with a duration of over 6 months, offering competitive pay. Key skills include Python, Hugging Face Transformers, and MLOps practices. Experience in healthcare technology and familiarity with HIPAA compliance is preferred. Remote work location.
🌎 - Country
United States
💱 - Currency
$ USD
-
💰 - Day rate
Unknown
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🗓️ - Date
October 10, 2025
🕒 - Duration
More than 6 months
-
🏝️ - Location
Remote
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📄 - Contract
Unknown
-
🔒 - Security
Unknown
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📍 - Location detailed
United States
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🧠 - Skills detailed
#Kubernetes #Azure #TensorFlow #Jenkins #Regression #FastAPI #Scala #Transformers #NoSQL #Python #Compliance #Cloud #A/B Testing #"ETL (Extract #Transform #Load)" #Azure SQL #BERT #GCP (Google Cloud Platform) #Deployment #GitHub #Hugging Face #PyTorch #AI (Artificial Intelligence) #Monitoring #AWS (Amazon Web Services) #Observability #ML (Machine Learning) #NLP (Natural Language Processing) #Security #Deep Learning #SQL (Structured Query Language) #FHIR (Fast Healthcare Interoperability Resources) #Docker #Databases
Role description
About Us
👏 Team from OpenAI, DeepMind, NASA, GoogleX, Tesla, and 2 physicians: 6 exits, 2 IPOs.
🔥 Our model outperforms Claude, Gemini, and GPT-4.5 on clinical benchmarks.
📈 400+ healthcare orgs signed in 16 months.
⚡️ $25M raised from YC, Amity Ventures, Sequoia scouts, and more.
🌎 $1T+ market opportunity. We’re going after all of it.
Role Overview
You will own the architecture, development, and continuous improvement of Sully.ai’s NLP models powering the Receptionist and Assistant agents. Working cross‑functionally with Product, Clinical, and Reliability Engineering, you’ll translate clinical workflows into robust conversational AI solutions that meet HIPAA‑level security and compliance requirements.
What You’ll Do
• Architect NLP Pipelines. Design end‑to‑end pipelines for intent detection, entity extraction, and dialogue management using Hugging Face Transformers.
• Fine‑Tune Transformer Models. Adapt state‑of‑the‑art architectures (e.g., BERT, GPT) on domain‑specific data to optimize receptionist and assistant workflows, leveraging prompt engineering and RAG techniques.
• Define Evaluation Frameworks. Establish benchmarks (F1‑score, ROUGE, MMLU) and A/B test protocols to measure dialogue accuracy, user satisfaction, and model latency.
• Deploy & Scale. Containerize models with Docker, serve via FastAPI, and orchestrate on Kubernetes for high availability and observability.
• Lead MLOps Best Practices. Build CI/CD pipelines for model training, testing, and versioning; integrate monitoring and alerting for data drift and performance regressions.
• Collaborate & Mentor. Partner with Product and Clinical teams to curate training data, refine user flows, and onboard new engineers into our NLP practice.
What You’ll Bring
• 5+ years of software engineering experience, with 3+ years focused on ML/NLP in production settings.
• Proficiency in Python and deep learning frameworks (PyTorch or TensorFlow), with hands‑on experience using Hugging Face Transformers.
• Demonstrated success in fine‑tuning and deploying transformer‑based models for conversational AI or related NLP applications.
• Experience building and scaling RESTful services with FastAPI, containerizing with Docker, and managing Kubernetes deployments.
• Strong analytical skills and familiarity with evaluation metrics for NLP systems (F1, ROUGE, MMLU).
• Excellent communication and collaboration skills in fast‑paced, cross‑functional teams.
Tech Stack
• Languages & Frameworks: Python, PyTorch/TensorFlow, Hugging Face Transformers.
• APIs & Services: FastAPI, Docker, Kubernetes, CI/CD (GitHub Actions, Jenkins).
• Cloud & Data: AWS/GCP/Azure, SQL/NoSQL databases.
• AI & MLOps: Prompt engineering, RAG, model versioning, monitoring & alerting.
Nice to Have
• Prior experience in healthcare technology or familiarity with FHIR and HIPAA compliance.
• Contributions to open‑source NLP projects or publications in top‑tier conferences.
• Experience with retrieval‑augmented generation (RAG) and prompt‑tuning techniques
Why Join Sully.ai?
🔥 Shape the Future of Healthcare: Build category-defining partnerships that enable doctors to focus on saving lives.
📈 Early-Stage Impact: Join early and play a critical role in shaping our partnership roadmap and overall company growth.
🌎 Remote-First Culture: Work with a talented, mission-driven team in a flexible, remote environment.
💰 Competitive Compensation: Enjoy a competitive salary, equity, and the opportunity to make a real difference.
🏆 Solve Scalability Challenges: Tackle complex challenges in a rapidly growing company, driving impactful change in healthcare.
Sully.ai is an equal opportunity employer. In addition to EEO being the law, it is a policy that is fully consistent with our principles. All qualified applicants will receive consideration for employment without regard to status as a protected veteran or a qualified individual with a disability, or other protected status such as race, religion, color, national origin, sex, sexual orientation, gender identity, genetic information, pregnancy or age. Sully.ai prohibits any form of workplace harassment.
About Us
👏 Team from OpenAI, DeepMind, NASA, GoogleX, Tesla, and 2 physicians: 6 exits, 2 IPOs.
🔥 Our model outperforms Claude, Gemini, and GPT-4.5 on clinical benchmarks.
📈 400+ healthcare orgs signed in 16 months.
⚡️ $25M raised from YC, Amity Ventures, Sequoia scouts, and more.
🌎 $1T+ market opportunity. We’re going after all of it.
Role Overview
You will own the architecture, development, and continuous improvement of Sully.ai’s NLP models powering the Receptionist and Assistant agents. Working cross‑functionally with Product, Clinical, and Reliability Engineering, you’ll translate clinical workflows into robust conversational AI solutions that meet HIPAA‑level security and compliance requirements.
What You’ll Do
• Architect NLP Pipelines. Design end‑to‑end pipelines for intent detection, entity extraction, and dialogue management using Hugging Face Transformers.
• Fine‑Tune Transformer Models. Adapt state‑of‑the‑art architectures (e.g., BERT, GPT) on domain‑specific data to optimize receptionist and assistant workflows, leveraging prompt engineering and RAG techniques.
• Define Evaluation Frameworks. Establish benchmarks (F1‑score, ROUGE, MMLU) and A/B test protocols to measure dialogue accuracy, user satisfaction, and model latency.
• Deploy & Scale. Containerize models with Docker, serve via FastAPI, and orchestrate on Kubernetes for high availability and observability.
• Lead MLOps Best Practices. Build CI/CD pipelines for model training, testing, and versioning; integrate monitoring and alerting for data drift and performance regressions.
• Collaborate & Mentor. Partner with Product and Clinical teams to curate training data, refine user flows, and onboard new engineers into our NLP practice.
What You’ll Bring
• 5+ years of software engineering experience, with 3+ years focused on ML/NLP in production settings.
• Proficiency in Python and deep learning frameworks (PyTorch or TensorFlow), with hands‑on experience using Hugging Face Transformers.
• Demonstrated success in fine‑tuning and deploying transformer‑based models for conversational AI or related NLP applications.
• Experience building and scaling RESTful services with FastAPI, containerizing with Docker, and managing Kubernetes deployments.
• Strong analytical skills and familiarity with evaluation metrics for NLP systems (F1, ROUGE, MMLU).
• Excellent communication and collaboration skills in fast‑paced, cross‑functional teams.
Tech Stack
• Languages & Frameworks: Python, PyTorch/TensorFlow, Hugging Face Transformers.
• APIs & Services: FastAPI, Docker, Kubernetes, CI/CD (GitHub Actions, Jenkins).
• Cloud & Data: AWS/GCP/Azure, SQL/NoSQL databases.
• AI & MLOps: Prompt engineering, RAG, model versioning, monitoring & alerting.
Nice to Have
• Prior experience in healthcare technology or familiarity with FHIR and HIPAA compliance.
• Contributions to open‑source NLP projects or publications in top‑tier conferences.
• Experience with retrieval‑augmented generation (RAG) and prompt‑tuning techniques
Why Join Sully.ai?
🔥 Shape the Future of Healthcare: Build category-defining partnerships that enable doctors to focus on saving lives.
📈 Early-Stage Impact: Join early and play a critical role in shaping our partnership roadmap and overall company growth.
🌎 Remote-First Culture: Work with a talented, mission-driven team in a flexible, remote environment.
💰 Competitive Compensation: Enjoy a competitive salary, equity, and the opportunity to make a real difference.
🏆 Solve Scalability Challenges: Tackle complex challenges in a rapidly growing company, driving impactful change in healthcare.
Sully.ai is an equal opportunity employer. In addition to EEO being the law, it is a policy that is fully consistent with our principles. All qualified applicants will receive consideration for employment without regard to status as a protected veteran or a qualified individual with a disability, or other protected status such as race, religion, color, national origin, sex, sexual orientation, gender identity, genetic information, pregnancy or age. Sully.ai prohibits any form of workplace harassment.