AI / ML Engineer at Numentica

About the Role 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. What You'll Build • 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 • Work primarily in the terminal \- if you're comfortable in vim\/neovim and live in the CLI, you'll fit right in Required Skills Core Technical (Non\-Negotiable) • 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 ML Domains (Must have strong experience in at least 2\-3 of these) • 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 Working Style (Critical) • 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 Nice to Have • 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) What We're NOT Looking For • Someone who needs extensive documentation before starting • Developers who only work with GUIs • People uncomfortable with ambiguity or rapid change • Engineers who need constant direction • Junior developers still learning ML fundamentals Our Stack Core: Python | PyTorch\/TensorFlow | Scikit\-learn | FastAPI\/Flask | Git | Bash\/PowerShell ML\/AI Tools: MLflow | Airflow\/Kubeflow | Azure AI | AWS SageMaker\/Bedrock | GCP Vertex AI | OCI AI Services Infrastructure: Docker | Kubernetes | AWS\/Azure\/GCP\/OCI | PostgreSQL | Azure DevOps | GitHub Actions Experience Level • 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) Why Join Us • Real impact: Your work directly affects our product and users • Technical freedom: Choose your tools, own your decisions • Fast feedback loops: See your code in production within days, not months • No red tape: Small team, direct access to leadership • Cutting edge: Work with latest ML\/AI tech, not maintaining legacy systems • Growth: Own entire ML systems end\-to\-end and influence technical direction Interview Process ​ 1. Quick call (30 min) \- culture fit, basic technical discussion 2. Technical challenge (take\-home, 2\-3 hours) \- build something real 3. Live problem solving (60 min) \- work through a realistic ML problem together 4. Team meet (30 min) \- meet potential teammates To Apply: Send your resume and briefly describe: 1. The most challenging greenfield ML project you've built 2. Which 2\-3 ML domains (from our list) do you have the most production experience in "}}],"isMobile":false,"iframe":"true","jobType":"Contract","applyName":"Apply Now","zsoid":"39633942","FontFamily":"Verdana, Geneva, sans\-serif","jobOtherDetails":[{"fieldLabel":"Location","uitype":1,"value":"Stassney, Texas"},{"fieldLabel":"Industry","uitype":2,"value":"IT Services"},{"fieldLabel":"City","uitype":1,"value":"Sealy"},{"fieldLabel":"State\/Province","uitype":1,"value":"Texas"},{"fieldLabel":"Zip\/Postal Code","uitype":1,"value":"77474"}],"headerName":"AI \/ ML Engineer","widgetId":"253104000000311040","isJobBoard":"false","userId":"253104000000051003","attachArr":[],"customTemplate":"4","isCandidateLoginEnabled":true,"jobId":"253104000018593001","FontSize":"12","googleIndexUrl":"https:\/\/numentica.zohorecruit.com\/recruit\/ViewJob.na?digest=vdse4pa3UG.8eZ1tXmZI9gwFePPOVtsqqHNw6CIHVCc\-&embedsource=Google","location":"Sealy","embedsource":"CareerSite","logoId":"mepjd1e421cc0c11d44a2baf2a875fb4a615d"}