AI ML Engineer at Numentica LLC

About the RoleWere looking for a sharp fast-moving AI/ML engineer who thrives in ambiguity and gets excited about buildingthings from scratch. Youll be tackling greenfield projects across various ML domains - whether thats NLPtime series forecasting recommendation systems or computer vision.The path isnt always clear and your ability to think on your feet and problem-solve in real-time will be critical.This isnt a role for someone who needs detailed specs and hand-holding. We need someone who can figure itout move fast and ship production-quality code.What Youll Build AI/ML systems from the ground up - youll 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 youre comfortable in vim/neovim and live in the CLI youll fit right inRequired SkillsCore 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 automationML Domains (Must have strong experience in at least 2-3 of these) NLP/LLMs: Experience with transformers (BERT GPT T5) RAG systems fine-tuning promptengineering or building LLM applications Time Series: Forecasting models anomaly detection sequential data modeling or real-time monitoringsystems Recommender Systems: Collaborative filtering ranking models personalization engines or contentrecommendations MLOps Tools: Production experience with MLflow Weights & Biases Kubeflow Airflow or similarplatforms Distributed Training: Large-scale model training multi-GPU/multi-node setups efficient dataparallelismWorking Style (Critical) CLI-first developer - youre comfortable (and prefer) working in the terminal Fast thinker - you can rapidly assess problems prototype solutions and iterate Problem solver - you dont need the answer handed to you; you figure it out Greenfield-ready - youre energized by building new things not just maintaining existing systems Self-directed - you can take ambiguous requirements and turn them into working solutionsNice 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 Were 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 fundamentalsOur StackCore: Python PyTorch/TensorFlow Scikit-learn FastAPI/Flask Git Bash/PowerShellML/AI Tools: MLflow Airflow/Kubeflow Azure AI AWS SageMaker/Bedrock GCP Vertex AI OCI AIServicesInfrastructure: Docker Kubernetes AWS/Azure/GCP/OCI PostgreSQL Azure DevOps GitHub ActionsExperience 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 directionInterview Process1. Quick call (30 min) - culture fit basic technical discussion2. Technical challenge (take-home 2-3 hours) - build something real3. Live problem solving (60 min) - work through a realistic ML problem together4. Team meet (30 min) - meet potential teammatesTo Apply: Send your resume and briefly describe:1. The most challenging greenfield ML project youve built2. Which 2-3 ML domains (from our list) do you have the most production experience inRequired Skills:AI ML EngineerRequired Education:AI ML Engineer Key Skills ASP.NET,Health Education,Fashion Designing,Fiber,Investigation Employment Type : Full Time Experience: years Vacancy: 1 Monthly Salary Salary: 40 - 40