September 20
πΊπΈ United States β Remote
π½ New York β Remote
β° Full Time
π‘ Mid-level
π Senior
π€ Machine Learning Engineer
AWS
Azure
Cloud
Docker
Google Cloud Platform
Kubernetes
Numpy
Pandas
PySpark
Python
PyTorch
Scikit-Learn
ServiceNow
Tensorflow
β’ Architect and develop enterprise-grade conversational AI solutions for leadership coaching. β’ Develop, design and implement improvements in user experience in conversational interactions leveraging LLMs in novel ways to advance product goals. β’ Evaluate and improve existing conversational (LLM-based) models across dimensions of effectiveness, scalability, and efficiency. β’ Implement, test, and deploy LLM-powered coaching agents that understand complex tasks, provide accurate and relevant responses, and adapt to diverse conversational contexts. β’ Integrate and manage diverse data sources to enhance the knowledge and contextual understanding of our AI coaching models. β’ Work with the product team to study user behavior and prioritize evolving product developments. β’ Experiment at a high velocity to optimize user experience. β’ Full stack - write, review and deploy code across back and front end as needed. β’ Streamlining data science processes to support rapid iteration and quality improvement. β’ Support other science and software development where required.
β’ Bachelor's degree in Computer Science, Engineering, Mathematics, related field, or equivalent experience. β’ 3+ years of professional experience (or equivalent) in software engineering, AI/ML development (ideally including a Master's or Ph.D. in Computer Science, ML, Data Science, or a related field). β’ Practical and theoretical knowledge of language systems in the areas of: conversational systems, NLP, and Information Retrieval with knowledge of relevant tools. β’ Strong software engineering skills with a track record of developing data-driven machine learning systems or products. β’ Proficiency in Python and relevant deep learning frameworks - both training (e.g. PyTorch, Tensorflow, JAX) and serving (e.g., Hugging Face TGI/Transformers/Adapters/outlines, vLLM). β’ Experience with cloud deployment of ML systems (e.g., AWS, GCP, Azure) including and open systems (e.g. Docker and Kubernetes) and their associated ML services. β’ Experience with Data Science tools and processes (e.g. NumPy, scikit-learn, Pandas, PySpark). β’ Familiarity with ML lifecycle tools like MLflow, Weights & Biases. β’ Hands-on experience building Generative AI-powered applications, including Large Language Models. β’ Strong analytical and problem-solving skills. β’ Ability to communicate complex ideas and concepts effectively. β’ Exposure to early-stage startups, preferably B2B SaaS.
β’ Ownership of projects and strategic priorities regardless of seniority in our learning-focused environment. β’ Strong ties to the executive team, a culture of transparency and engagement with strategic decisions. β’ Options from day one, which means you will be on the ownership track right away. β’ Competitive salary and equity packages. β’ Comprehensive health coverage (medical, dental, and vision) from day 1. β’ Provision of anything you need to be successful - learning tools, hardware, office equipment, software. β’ 401k optionality for US based employees. β’ Generous PTO, company-wide R&R shutdowns and paid leave for parents. β’ A WFH stipend, phone stipend and support to work in a We Work or other space as preferred.
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