- Company Name
- SIDRAM TECHNOLOGIES
- Job Title
- AI Engineer - w2
- Job Description
-
Job Title: AI Engineer
Role Summary: Design, develop, and deploy AI/ML solutions that automate decision‑making and enhance operational efficiency for a global organization’s environmental and social initiatives.
Expectations: Deliver scalable, ethical AI models, integrate them into existing systems, ensure compliance with data governance, train stakeholders, and provide ongoing support and maintenance.
Key Responsibilities
- Collaborate with cross‑functional teams to identify AI opportunities and translate business requirements into technical specifications.
- Train, validate, and optimize machine learning, NLP, computer vision, and large language models (LLMs).
- Fine‑tune Retrieval‑Augmented Generation (RAG) systems and implement GenAI solutions.
- Develop and deploy models to cloud environments (AWS, Azure, GCP) using MLOps tools (MLflow, Docker, GitOps).
- Manage data pipelines: collect, clean, preprocess structured and unstructured data, including geospatial data; monitor data quality, bias, and drift.
- Deploy models via REST APIs and manage vector databases, NoSQL, and RDBMS backends.
- Monitor model performance, troubleshoot issues, and refine deployments for accuracy.
- Produce technical documentation, user guides, and training materials; conduct stakeholder training sessions.
- Advise on AI strategy, governance, and policy implications; contribute to the organization’s AI roadmap.
Required Skills
- Proficient in Python, TensorFlow, PyTorch, and NLP frameworks (spaCy, Hugging Face, etc.).
- Hands‑on experience with LLMs, RAG, NLP, and generative AI.
- Expertise in MLOps (MLflow, Docker, CI/CD pipelines).
- Cloud platform proficiency (Azure AI, Google Vertex AI, AWS AI services).
- Strong knowledge of vector databases, NoSQL (MongoDB, Cassandra) and relational databases.
- RESTful API development and API management.
- Data engineering: ETL, feature engineering, data cleaning, bias detection, and drift monitoring.
- Analytical and problem‑solving abilities; excellent communication and teamwork skills; strategic and innovative mindset.
Required Education & Certifications
- Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field.
- Minimum 3 years’ experience in AI/ML model development and deployment.
- Preferred certifications: Microsoft Certified: Azure AI Engineer Associate, Google Machine Learning Engineer, SAFe Agile Software Engineer (ASE), Certificate in AI Ethics.
District of columbia, United states
On site
Junior
28-11-2025