Lead ML Research and Development: Drive the research, development, and optimization of machine learning models, focusing on solving real-world business problems through advanced ML techniques.
Architect Novel Training and Fine-Tuning Methodologies: Design, implement, and iterate on advanced training protocols, fine-tuning processes, and optimization strategies, particularly for Language Models (LLMs).
Evaluate Model Performance and Innovation: Develop and refine techniques for assessing and enhancing the effectiveness of ML models, focusing on accuracy, scalability, and adaptability to dynamic enterprise requirements.
Feedback System Design for Continuous Learning: Create systems that incorporate user and system feedback to iteratively improve model performance over time.
Cross-Functional Collaboration: Work closely with product teams and domain experts to translate business needs into research questions and actionable ML strategies.
Stay Current on ML Advancements: Actively monitor the latest research in ML and NLP, integrating cutting-edge practices and methodologies into our development pipeline.
Mentor and Guide Team Members: Provide technical guidance to junior researchers, fostering a culture of continuous learning, experimentation, and research-driven development.

Requirements

Expertise in ML Model Training and Optimization: Proven experience with ML research, including designing and evaluating novel training methodologies, model architectures, and optimization techniques.
Deep Knowledge of Language Model Fine-Tuning: Demonstrated proficiency in customizing and fine-tuning language models to meet specific use cases, with experience in models such as GPT, BERT, or similar frameworks.
Proficiency in ML Frameworks: Strong understanding of machine learning and NLP frameworks like TensorFlow, PyTorch, or similar, with the ability to design and implement custom model architectures.
Programming Skills: Proficiency in Python with an emphasis on writing efficient, maintainable, and scalable code.
Research Communication Skills: Ability to present complex technical concepts to both technical and non-technical stakeholders, highlighting the business impact of ML innovations.
Educational Background: A Master’s or PhD in Computer Science, Machine Learning, or a related field, with a focus on ML research.
Impactful ML Solution Delivery: Proven track record of delivering ML solutions that have made significant real-world impact, ideally within an enterprise or production setting.
Active Secret or Top Secret Clearance.

Benefits

100% employer-paid, comprehensive health care including medical, dental, and vision for you and your family.
Paid maternity and paternity for 14 weeks at employees' normal pay.
Unlimited PTO, with management approval.
Opportunities for professional development and continued learning with educational reimbursements.
Optional 401K, FSA, and equity incentives available.
Mental health benefits through TARA Mind.

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard skills

ML model trainingmodel optimizationlanguage model fine-tuningTensorFlowPyTorchPythoncustom model architecturesmodel performance evaluationscalability techniquesNLP frameworks

Soft skills

cross-functional collaborationtechnical guidanceresearch communicationmentoringcontinuous learningproblem-solvinginnovationadaptabilityteamworkpresentation skills

Certifications

Master’s in Computer SciencePhD in Machine LearningActive Secret ClearanceActive Top Secret Clearance