ML Engineer

A fast-growing company that is developing a centralized platform to help clients discover, assess, and collect key embeddings, is looking for a ML Engineer. The engineer will be in charge of building data architectures and pipelines that follow technical guidelines and organizational objectives, testing them, and keeping them optimized. With the help of the company's cutting-edge technology, businesses may switch from complex, pricey models to simpler, open-source models without sacrificing accuracy. This is an amazing opportunity for engineers who are passionate about proving themselves and working in a challenging environment.

Job Responsibilities:

• 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