Senior Machine Learning Engineer

Senior Machine Learning Engineer

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About Us

TxR Ventures is building an AI-powered platform that reimagines how students learn and prepare for their careers. By combining intelligent systems with thoughtful design, we are creating scalable tools for deep, multimodal learning. Our mission is to improve student outcomes and employability through intelligent, personalized, and data-driven solutions.

Role Overview

We are seeking a Senior Machine Learning Engineer to lead core ML development across our learning platform. You will design, build, and maintain high-quality ML systems that power personalized student experiences. This includes optimizing and integrating our proprietary models, developing robust evaluation frameworks, and working closely with our backend team to ensure reliable, observable, and scalable production deployments.

The role requires strong end-to-end ownership, rigorous engineering practices, and deep familiarity with modern ML techniques, multimodal systems, and evaluation methodologies. You'll take ownership of critical ML infrastructure that directly impacts how students learn and progress through our platform.

Key Responsibilities

• Build, refine, and deploy LLM-based systems using models from top providers for structured reasoning pipelines, and controlled output processing

• Develop multi-step, agentic processing workflows that incorporate orchestration, validation layers, and iterative refinement mechanisms

• Design and maintain evaluation pipelines with custom metrics, benchmarking frameworks, observability instrumentation, and experiment tracking

• Implement guardrails, consistency checks, and hallucination-control strategies to ensure reliable, predictable, and high-quality model outputs

• Build targeted computer vision components using established frameworks (YOLO, OpenCV, OCR) and integrate them into broader ML workflows

• Construct scalable ML inference pipelines incorporating batching, caching, monitoring, reliability safeguards, and backend integration

• Translate product and engineering requirements into well-structured ML designs, ensuring clarity, feasibility, and alignment with platform standards

• Define and enforce best practices around reproducibility, model lifecycle control, regression tracking, and code quality

• Mentor junior engineers in ML development, evaluation methodology, and deployment best practices

Required Skills

• 5+ years of ML engineering experience in production environments

• Strong expertise in LLM development, prompt-driven workflows, and structured reasoning

• Experience with LangChain or LlamaIndex for LLM orchestration

• Experience with W&B and Langfuse for experiment tracking and observability

• Experience with RAG techniques and vector search (FAISS or Pinecone)

• Strong Python skills and experience with PyTorch or TensorFlow

• Experience with core CV tools (YOLO, OpenCV, OCR libraries)

• Strong foundations in evaluation methodology, experiment design, and data quality

• High engineering standards around testing, reliability, documentation, and maintainability