Role overview

Qualifications

Advanced degree (MS or PhD) in Electrical Engineering, Computer Sciences, Mathematics, or a related field
Publications in leading AI conferences (e.g., CL, NeurIPS, ICML, ICLR)
Proficient programming skills and experience in developing machine learning solutions
Familiarity with deep learning frameworks (e.g., PyTorch, Jax, TensorFlow)

Responsibilities

Push the boundaries of medical NLP research, focusing on conversation summarization and evidence extraction
Engage with the broader research community by disseminating original research findings
Tackle significant challenges and innovate state-of-the-art methodologies
Utilize feedback from healthcare professionals for continuous improvement

Key facts

Remote from: Georgia (USA)
Full time
NLP Engineer
English

Hard skills

Machine Learning Natural Language Processing (NLP) Deep Learning Statistical Analysis Information Extraction Evaluation Strategy Laboratory Techniques Computer Programming Software Prototyping Program Implementation PyTorch (Machine Learning Library) JAX-WS TensorFlow

Other skills

Critical Thinking
Problem Solving

About the company

TechStarsGroup LLC

Staffing & Recruiting

TechStarsGroup specializes in the recruitment and placement of information technology professionals for leading SaaS, Health Information Technology, Payments, and e-Commerce software companies . Our services cater to a diverse range of venture backed startups and middle market software product companies. With a proven model focused on networking within the 85% of the professionals "open to other opportunities but not actively in a job search", TechStarsGroup breaks the mold of the recruiting industry practices of focusing on the most readily available candidates. If you are a client in need of adding a key player to your team, TechStars recruiting process compliments your internal efforts and exposes you to candidates you would otherwise never see. If you are a professional looking to make a change TechStars will get to know you and what your trying to accomplish and only present opportunities consistent with those goals.

Company details

IndustryStaffing & Recruiting

Company size2 - 10

Links

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Job description

Machine Learning / NLP Research Scientist - (REMOTE)

(multiple opportiunities at various levels)

Our client is at the forefront of applying machine learning research to transform the way medical conversations are understood and utilized. We are in search of research scientists who are proficient in machine learning and natural language processing to join our innovative team. The ideal candidate will possess a deep understanding of foundation models, a keen interest in healthcare applications, and the ability to think critically and solve complex problems. Our work is deeply rooted in research, with every member of our team contributing to the development of real-world applications that significantly benefit healthcare professionals.

**What You'll Do**

- Push the boundaries of medical NLP research, focusing on conversation summarization, evidence extraction, outcome prediction, and developing new evaluation techniques and experimental approaches.

- Engage with the broader research community by disseminating original research findings and insights.

- Tackle significant challenges, set benchmarks, innovate state-of-the-art methodologies, and integrate them into practical applications.

- Utilize feedback from healthcare professionals to drive continuous improvement and innovation in our solutions.

- Approach ambiguous challenges and uncertain results with a results-driven mindset.

**What You'll Bring**

- A solid research foundation, evidenced by publications and an advanced degree (MS or PhD) in Electrical Engineering, Computer Sciences, Mathematics, or a related field.

- Contributions to leading AI conferences (e.g., *CL, NeurIPS, ICML, ICLR) through high-impact publications.

- Demonstrated real-world impact via open source contributions and the deployment of technologies.

- Proficient programming skills and experience in developing, prototyping, and implementing machine learning solutions in a production environment.

- Familiarity with deep learning frameworks (e.g., PyTorch, Jax, TensorFlow), experience with multi-GPU training, and a strong capability in statistical analysis of both observational and experimental data.