Machine Learning Engineer

United States                ·             Full time

About the job

About Twill

Twill is a global software-enabled healthcare platform with a mission to improve the mental and physical health of people everywhere. Our evidence-based programs and supportive communities help people manage life challenges and chronic conditions, while providing access to solutions such as telehealth, AI-powered coaching, and therapeutics. We empower people wherever they are in their care journey to adopt healthy behaviors, and our solutions are used by enterprises, health plans, health systems, pharmaceutical manufacturers, and individuals around the world. Today, the Twill platform is available globally in 10 languages and covers more than 18 million lives. In 2023, Twill was named one of Built In’s 100 Best Places to Work in the U.S.

Twill’s Artificial Intelligence (AI) team utilizes natural language processing (NLP) and deep learning algorithms to develop the next generation of conversational agents in clinical applications. This role will join a nimble team of computer scientists and clinical psychologists.

Responsibilities

• Design, develop, and deploy machine learning models into production, focusing on high availability, low latency, and scalability.
• Conduct advanced data analysis and complex designs algorithms.
• Collaborate with cross-functional teams to understand company needs and devise possible solutions
• Keep abreast of developments in machine learning and artificial intelligence.
• Implement best practices to improve existing machine-learning infrastructure.
• Create and maintain technical documentation.

Qualifications

• Strong educational background in machine learning, data science, computer science, or equivalent, including hands-on projects and coursework in deep learning, machine learning, natural language processing, and statistical pattern recognition.
• Strong programming skills in Python and familiarity with libraries like Pandas, NumPy, scikit-learn, PyTorch, PyTorch Lightning, and Hugging Face’s Accelerate.
• Proven experience working with large language models (LLMs) such as Masked Language Models (MLMs), Causal Language Models (CLMs) like GPT.
• Demonstrated expertise in developing and maintaining machine learning models, data pipelines, and architectures.
• Experience with Streamlit or other frameworks for building ML-powered web applications.
• Excellent understanding of machine learning techniques and algorithms.
• Experience with version control tools such as Git.

Preferred Qualifications

• Experience with conversational agents and natural language processing (NLP) is a significant plus.
• Experience in developing, implementing, and maintaining recommendation systems with a deep understanding of collaborative filtering, content-based filtering, and hybrid methods.
• Familiarity with cloud services (AWS, GCP, Azure) and containerization technologies (Docker, Kubernetes).
• Experience in deploying machine learning models using CI/CD pipelines.

Please click here to apply.