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AI Engineer (LLMs / Machine Learning / MLOps)
About Us
Tech9 is shaking up a 20-year-old industry, and we're not slowing down. Recognized by Inc. 5000 as one of the nation's fastest-growing companies, we are dedicated to building innovative, high-quality software solutions. Our team is passionate about delivering technology that makes an impact. We offer a 100% remote working environment with a collaborative and supportive culture, allowing you to focus on what you do best.
Role Overview
We’re looking for a highly skilled and hands-on AI Engineer with deep experience in LLMs, machine learning, and end-to-end AI pipelines. This role is ideal for someone who thrives in a fast-paced, startup-like environment, is passionate about solving complex problems using the latest in AI, and can collaborate across teams to turn models into real products.
You will work closely with engineers, product managers, and designers to build intelligent systems that leverage the power of LLMs, classic ML, and data-driven insight.
Responsibilities
- Design, train, and deploy machine learning models (supervised, unsupervised, and semi-supervised) for a variety of use cases.
- Integrate Large Language Models (LLMs) into products using frameworks like LangChain, LangGraph, or custom agents.
- Fine-tune transformer-based models using techniques like LoRA, QLoRA, or full fine-tuning on domain-specific datasets.
- Implement RAG (Retrieval-Augmented Generation) pipelines with vector databases (e.g., Pinecone, Weaviate, FAISS).
- Collaborate with engineering teams to integrate models into production using MLOps best practices (CI/CD, monitoring, observability).
- Design and build evaluation frameworks for AI models to ensure performance, quality, and safety over time.
- Contribute to prompt engineering and prompt optimization strategies to improve model performance.
- Work across cross-functional teams to drive AI-first product initiatives from prototype to production.
Required Qualifications
- Strong programming skills in Python and experience with ML libraries (NumPy, Pandas, Scikit-learn, SciPy, StatsModels).
- Hands-on experience with ML frameworks like PyTorch and/or TensorFlow.
- Solid understanding of math, probability, statistics, and algorithms.
- Proven experience working with transformer-based models and NLP techniques.
- Familiarity with computer vision tasks like image recognition, object detection, or generation (nice to have).
- Experience with OpenAI APIs, Hugging Face Transformers, and LLM integration in real-world projects.
- Experience with cloud platforms like AWS, Azure, or GCP.
- Skilled in data engineering: data collection, cleaning, preprocessing, and transformation.
- Experience with Docker, Kubernetes, and Git for model lifecycle and reproducibility.
- Familiarity with DevOps/MLOps tools for model deployment, CI/CD, and monitoring in production environments.
- Excellent communication skills and a strong ability to work cross-functionally.
Preferred Experience
- Prior use of LangChain, LangGraph, or custom agent frameworks.
- Knowledge of vector databases and semantic search engines.
- Experience evaluating and monitoring model drift, safety, and performance in production.
Hiring Process
- Screening Call – Situational and behavioral questions to understand your ownership, adaptability, and collaboration style.
- Technical Interview 1 – Conducted with a senior AI engineer.
- Technical Interview 2 – Conducted with an AI engineer and the hiring manager.
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