Machine Learning Research Engineer

About the role

FL105 is actively seeking a highly skilled Machine Learning Research Engineer to join their team. This role involves designing, developing, and implementing advanced machine learning techniques to create essential psychological tools. The ideal candidate will possess a comprehensive understanding of machine learning, reinforcement learning from human feedback, supervised fine-tuning, and computational sciences. They will work in a fast-paced, innovative environment, collaborating with multidisciplinary teams to push the boundaries of AI applications in psychological health and related fields. The position offers an exciting opportunity to contribute to cutting-edge research and practical solutions that can have a meaningful impact on mental health technologies.

Key facts

What you'll do

• Develop and implement machine learning applications that leverage large language models to address complex problems in psychological wellbeing and mental health.
• Collaborate closely with psychology and neuroscience experts to translate interdisciplinary insights into computational models and algorithms.
• Contribute to research and development efforts in context engineering, agentic AI, and learning from human feedback to improve model capabilities and applicability.
• Design and build scalable systems for data collection, annotation, and labeling, ensuring high-quality training data for machine learning models.
• Develop training pipelines and fine-tuning techniques to adapt large language models for specific psychological tasks and applications.
• Deploy machine learning models into production environments, ensuring robustness, efficiency, and scalability.
• Conduct experiments, evaluate model performance, and iterate on algorithms to optimize results.
• Present research findings, technical progress, and project updates to internal teams and external stakeholders.
• Work with engineering teams to integrate machine learning solutions into user-facing products and services.
• Stay current with the latest advancements in machine learning, natural language processing, and related fields, applying new techniques as appropriate.
• Document methodologies, experiments, and results thoroughly to support reproducibility and knowledge sharing across teams.
• Contribute to the ongoing development of best practices and standards for machine learning research within the organization.

Requirements

• A master's degree or higher in computer science, machine learning, artificial intelligence, or a related field is preferred; however, exceptional candidates without formal degrees will also be considered.
• Strong foundational knowledge of machine learning, deep learning, and natural language processing techniques.
• Proven experience deploying large language model applications in production environments, with familiarity in frameworks such as PyTorch, vLLM, and LangGraph.
• Proficiency in Python programming language, along with experience using relevant libraries and tools for machine learning development and data processing.
• Experience working with large-scale datasets, data labeling, and evaluation methodologies.
• Ability to work independently, manage multiple tasks, and adapt to shifting project priorities in a fast-paced environment.
• Excellent communication skills, capable of explaining complex technical concepts to non-technical stakeholders.
• Critical thinking and problem-solving skills, with a focus on experimental design and iterative improvement.
• Prior experience in a startup or innovative research environment is advantageous but not mandatory.
• Knowledge of reinforcement learning techniques from human feedback is a plus.

Nice to have

• Publications in leading machine learning or natural language processing conferences such as NeurIPS, ICML, ACL, or EMNLP.
• Experience working on interdisciplinary projects that combine AI with psychology, neuroscience, or behavioral sciences.
• Familiarity with deploying and optimizing large language models for real-world applications.
• Understanding of ethical considerations and safety measures related to AI deployment in sensitive domains like mental health.

Skills & tools

• Machine learning frameworks: PyTorch, vLLM, LangGraph
• Programming language: Python
• Data processing and evaluation tools for large datasets and model performance assessment
• Version control systems and collaborative development tools

Practical notes

• The salary for this position ranges from $120,000 to $192,500, depending on the candidate's skills, experience, and qualifications.
• The company offers comprehensive healthcare benefits, an annual incentive program, retirement plans, and various additional perks to support employee well-being.
• Applications will be accepted until the position is filled, so early submission is encouraged.
• This role is based on-site in Cambridge, MA, and requires the candidate to work at the company's physical office location.
• The organization is committed to fostering a diverse and inclusive workforce and encourages all qualified candidates to apply, regardless of background or identity.
• Candidates should be prepared to engage in a collaborative environment that values innovation, scientific rigor, and practical impact.
• The position involves working closely with multidisciplinary teams, including psychologists, neuroscientists, and engineers, to develop impactful AI solutions.
• The organization emphasizes ethical AI development and responsible deployment, especially in sensitive areas like mental health.