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Senior AI/ML Engineer
Actively Hiring
Full-time Posted about 4 hours ago
Responsibilities
- check_circle Develop, deploy, and optimize machine learning and deep learning models.
- check_circle Build AI solutions for NLP, computer vision, predictive analytics, and intelligent automation.
- check_circle Integrate AI services into enterprise applications and internal platforms.
- check_circle Develop LLM-based applications, AI copilots, and RAG solutions.
- check_circle Implement prompt engineering, model evaluation, embeddings, and semantic search.
- check_circle Optimize model performance, scalability, and cost.
- check_circle Design and deploy autonomous and multi-agent AI systems.
- check_circle Develop agent orchestration, planning, reasoning, memory, and tool integration.
- check_circle Implement human-in-the-loop approvals and enterprise workflow automation.
- check_circle Build CI/CD pipelines for AI models and agents.
- check_circle Monitor AI systems for performance, drift, hallucinations, security, and reliability.
- check_circle Manage model versioning, deployment, observability, and lifecycle operations.
- check_circle Implement AI governance, model risk management, and Responsible AI practices.
- check_circle Maintain model documentation, validation, audit readiness, and compliance.
- check_circle Ensure fairness, traceability, maintainability, privacy, and regulatory adherence.
- check_circle Govern AI agent lifecycle, identity, access, and runtime controls.
- check_circle Implement guardrails, audit logging, and secure integration with enterprise systems.
- check_circle Protect AI solutions against prompt injection, data leakage, and adversarial attacks.
- check_circle Work with business, engineering, security, and architecture teams to deliver AI solutions.
- check_circle Mentor team members and promote AI engineering standards and best practice
Basic qualifications
- Machine Learning, Deep Learning, NLP, Computer Vision
- Predictive Analytics, Feature Engineering, Model Optimization
- Large Language Models (LLMs)
- Retrieval-Augmented Generation (RAG)
- Prompt Engineering
- Embeddings and Semantic Search
- Fine-tuning Foundation Models
- Autonomous and Multi-Agent Systems
- Agent Orchestration
- Planning and Reasoning
- Memory Management
- Tool Calling
- Human-in-the-Loop (HITL)
- Model Context Protocol (MCP)
- PyTorch
- TensorFlow
- Scikit-learn
- Hugging Face
- LangChain
- LangGraph
- LlamaIndex
- AutoGen
- CrewAI
- Semantic Kernel
- Microsoft Azure AI Foundry
- Azure Machine Learning
- AWS Bedrock
- Amazon SageMaker
- Google Vertex AI
- Docker
- Kubernetes
- Terraform
- SQL
- PostgreSQL
- MongoDB
- Apache Spark
- Vector Databases
- REST APIs
- FastAPI
- MLflow
- Kubeflow
- Azure ML Pipelines
- GitHub Actions
- Azure DevOps
Tags & Focus Areas
Contract Ai Ai Engineer Machine Learning Deep Learning Computer Vision Mlops Robotics Generative Ai
About DICETEK LLC
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