Machine Learning Engineer/Applied Researcher

About The Role: As a Machine Learning Engineer/Applied Researcher, you will be at the forefront of our efforts to train and fine-tune Large Language Models. You will work closely with our Research and Engineering teams to develop, implement, and optimize training strategies that enhance the performance and capabilities of our LLMs. Your expertise in modern supervised fine-tuning techniques will be crucial in pushing the boundaries of what our models can achieve.

What You’ll Do:

• Develop and implement supervised fine-tuning techniques including instruct tuning, DPO, KTO, and other advanced methods.
• Train and fine-tune Large Language Models to improve performance, accuracy, and generalization capabilities.
• Collaborate with cross-functional teams to design and execute experiments for validating and benchmarking model performance.
• Optimize training pipelines for efficiency and scalability, ensuring the best use of computational resources.
• Stay current with the latest research and developments in Machine Learning and AI, incorporating best practices into our training processes.
• Contribute to development of tools and frameworks that facilitate efficient model training and merging.
• Document research findings and technical processes, communicating results to both technical and non-technical stakeholders.

What We’re Seeking:

• Master’s or PhD in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
• Proven experience in training Large Language Models and applying modern supervised fine-tuning techniques, including instruct tuning, DPO, KTO, or other advanced methods.
• Strong programming skills in Python with familiarity in Machine Learning frameworks such as TensorFlow, PyTorch, or similar.
• Solid understanding of Machine Learning algorithms, model optimization, and performance evaluation metrics.
• Ability to design and conduct experiments, analyze results, and iterate on model improvements.
• Experience with distributed training environments and large-scale data processing, along with MLOps practices and tools for managing Machine Learning workflows.
• Prior experience in a startup environment or a fast-paced, dynamic work setting.
• Contributions to the AI/ML research community through publications or open-source projects.
• Excellent problem-solving skills and strong communication skills, with the ability to explain complex technical concepts to both technical and non-technical stakeholders.

About Arcee.AI: Arcee.AI emerged from the brainstorming of three co-founders – Mark McQuade, Jacob Solawetz, & Brian Benedict – who envisioned a platform that would allow companies to use SLMs to fuel innovation while still retaining full control over their data and models. Our vision is based on deep knowledge of both the technical and business aspects of AI and machine learning, gained via leading roles in companies including Hugging Face, Roboflow, and Tecton. Since emerging from stealth in September 2023, we have seen a market confirmation of the need for our easy-to-use platform for creating performant and efficient custom LLMs, also known as Small Language Models (SLMs). Following our Seed Round in January 2024 and Series A in July, we take pride in empowering our expanding customer base, driving business value and innovation across enterprises globally.

Equal Opportunity: We are an Equal Opportunity Employer, offering equal opportunity to all regardless of race, religion, gender identity, sexual orientation, age, citizenship, marital status, disability, and more. We encourage candidates who feel they would be a good fit to apply, even if they don't meet all listed qualifications.

Compensation: We offer competitive salaries, equity, and benefits, basing our compensation on location, role, level, as well as the candidate’s experience and overall qualifications.