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Description
Role Overview We're looking for a talented Machine Learning Engineer with 3+ years of experience to join our growing AI team. This role will play a central part in developing our real-time feedback engine, integrating and fine-tuning LLMs, and spearheading the training and deployment of custom and small language models (SLMs). Key Responsibilities Build and deploy scalable real-time inference systems using FastAPI and AWS. Fine-tune and integrate large language models (LLMs) like Claude 3.5 Sonnet via Amazon Bedrock. Lead or contribute to the training, fine-tuning, and evaluation of proprietary Small Language Models (SLMs). Build ML pipelines for preprocessing multimodal data (audio, transcript, slides). Collaborate with backend, design, and product teams to bring intelligent features into production. Optimize models for speed, efficiency, and edge/cloud deployment. Contribute to MLOps infrastructure for versioning, deployment, and monitoring of models. Required Qualifications 3+ years of experience in applied ML, including model deployment and training. Strong proficiency in Python, PyTorch, Transformers, and model training frameworks. Experience deploying APIs using FastAPI and integrating models in production. Experience fine-tuning LLMs (e.g., OpenAI, Claude, Mistral) and SLMs for specific downstream tasks. Familiarity with AWS services (S3, Bedrock, Lambda, SageMaker). Strong grasp of data pipelines, performance metrics, and model evaluation. Comfort working with multimodal datasets (text, audio, visual). Bonus Points Experience with Whisper, TTS systems (e.g., Polly), or audio signal processing. Background in building or fine-tuning SLMs for performance-constrained environments. Familiarity with MLOps tooling (MLflow, Weights & Biases, DVC). Experience with Redis, WebSockets, or streaming data systems. Perks and Benefits Attractive remuneration (competitive with market, based on experience and potential). Fully remote work – we’re a truly distributed team. Flexible working hours – we value output over clocking in. Health & wellness perks, learning stipends, and regular team retreats. Opportunity to work closely with passionate founders and contribute from Day 1. Be a core part of a fast-growing, high-impact startup with a mission to transform education. We look forward to receiving your application! Show more Show less
