ML Engineer

• Address continuous integration, fix systemic issues, keep an eye on the data ecosystem, develop scaling strategies, and support data management and governance
• Activate and keep an eye on automated data controls
• Ensure that ideas are offered to increase the effectiveness and efficiency of the data ecosystem
• Manage cyclical production releases, keep documentation accurate and current for each solution, and alert stakeholders to any data concerns

Job Requirements:

• Bachelor s/Master s degree in Engineering, Computer Science (or equivalent experience)
• At least 4+ years of relevant experience as a Machine Learning Engineer
• 3-4+ years in machine learning roles building, testing, and deploying language models over the course
• 4+ years of experience working with Python, AWS, and Machine Learning technologies
• Some familiarity with LLM, Tensorflow, and PyTorch is desirable
• Solid understanding of the fundamental technologies used in ML and LLM, including the Python ecosystem, vector databases (Weaviate, Pinecone), Tensorflow/Pytorch, Huggingface, Langchain, and AWS (SageMaker, etc.).
• Working knowledge of the ideas of LLM, such as prompt engineering, transformers, reinforcement learning from human feedback (RLHF), model fine-tuning, and embeddings
• Some experience with published papers at ML/NLP conferences like ACL, EMNLP, CoNLL, ICML, RecSys, etc. is desirable
• Solid experience of working with data processing tools at scale (Python, Spark, Hadoop, etc.) is preferred
• In-depth knowledge of working with containerized cloud environments (Docker, Kubernetes, AWS/GCP) is nice to have
• Prior experience working as an early employee at a high-growth startup with relevant experience, and the ability to ship quickly
• Must be generalists with the ability to quickly assemble components to make things function
• Extensive knowledge of search, recommendation, and retrieval methods
• Fluent in spoken and written English communication