AI / ML Engineer

Numentica LLC•Sealy, TX

28d

About The Position

We're looking for a sharp, fast-moving AI/ML engineer who thrives in ambiguity and gets excited about building things from scratch. You'll be tackling greenfield projects across various ML domains - whether that's NLP, time series forecasting, recommendation systems, or computer vision. The path isn't always clear, and your ability to think on your feet and problem-solve in real-time will be critical. This isn't a role for someone who needs detailed specs and hand-holding. We need someone who can figure it out, move fast, and ship production-quality code.

Requirements

Python - 3-5+ years production experience, this is your primary language
AI/ML Production - Built and deployed 2-3+ ML models serving real users, not just experiments
Cloud Platforms - Experience with AWS, Azure, GCP, or OCI for deploying and managing ML workloads. We leverage AI/ML tools across all major cloud providers (Azure AI, AWS SageMaker/Bedrock, GCP Vertex AI, OCI AI Services)
DevOps - Docker and Kubernetes experience
Databases - SQL (PostgreSQL, MySQL) and NoSQL/vector databases
Scripting - Proficient in both Bash and PowerShell for automation
NLP/LLMs: Experience with transformers (BERT, GPT, T5), RAG systems, fine-tuning, prompt engineering, or building LLM applications
Time Series: Forecasting models, anomaly detection, sequential data modeling, or real-time monitoring systems
Recommender Systems: Collaborative filtering, ranking models, personalization engines, or content recommendations
MLOps Tools: Production experience with MLflow, Weights & Biases, Kubeflow, Airflow, or similar platforms
Distributed Training: Large-scale model training, multi-GPU/multi-node setups, efficient data parallelism
CLI-first developer - you're comfortable (and prefer) working in the terminal
Fast thinker - you can rapidly assess problems, prototype solutions, and iterate
Problem solver - you don't need the answer handed to you; you figure it out
Greenfield-ready - you're energized by building new things, not just maintaining existing systems
Self-directed - you can take ambiguous requirements and turn them into working solutions
3-5+ years in AI/ML engineering roles
Proven track record of shipping 0-to-1 ML projects
Production ML experience (not just research or coursework)

Nice To Haves

CI/CD Experience: Azure DevOps, GitHub Actions, Jenkins, or similar automation pipelines
Computer Vision: Production CV experience with PyTorch/TensorFlow, OpenCV, object detection, segmentation, or real-time inference
Additional Languages: Go or Rust experience for performance-critical components
Feature stores (Feast, Tecton) or advanced feature engineering
Model optimization: quantization, pruning, knowledge distillation
Edge deployment or resource-constrained model deployment
Experiment frameworks for A/B testing ML models
Contributions to open-source ML projects
Real-time streaming data processing (Kafka, Kinesis)

Responsibilities

AI/ML systems from the ground up - you'll own projects from conception to production
Scalable ML pipelines and data workflows
Production-grade models serving real users at scale
MLOps infrastructure for training, deployment, and monitoring
Internal tooling that makes the team more efficient