Job Title: Developer Premium II - AI Engineer
Location: Washington, DC
Duration: 7 Months with long term extension
Hybrid Onsite: 4 days per week from Day 1, with a full transition to 100% onsite anticipated soon.
AI Engineer: The AI Engineer will play a pivotal role in designing, developing, and deploying artificial intelligence solutions that enhance operational efficiency, automate decision-making, and support strategic initiatives for the environmental and social specialists within the client. This role is central to the VPU s digital transformation efforts and will contribute to the development of scalable, ethical, and innovative AI systems.
Qualifications and Experience
Education: Bachelor s or Master s degree in Computer Science, Data Science, Engineering, or related field.
Experience:
- Minimum 3 years of experience in AI/ML model development and deployment.
- Experience with MLOps tools (e.g., MLflow), Docker, and cloud platforms (AWS, Azure, Google Cloud Platform).
- Proven track record in implementing LLMs, RAG, NLP model development and GenAI solutions.
Technical Skills:
- Skilled in Azure AI/Google Vertex Search, Vector Databases, fine-tuning the RAG, NLP model development, API Management (facilitates access to different sources of data)
- Proficiency in Python, TensorFlow, PyTorch, and NLP frameworks.
- Expertise deep learning, computer vision, and large language models.
- Familiarity with REST APIs, NoSQL, and RDBMS.
Certifications (Preferred):
- Microsoft Certified: Azure AI Engineer Associate
- Google Machine Learning Engineer
- SAFe Agile Software Engineer (ASE)
- Certification in AI Ethics
Objectives of the Assignment:
- Develop and implement AI models and algorithms tailored to business needs.
- Integrate AI solutions into existing systems and workflows.
- Ensure ethical compliance and data privacy in all AI initiatives.
- Support user adoption through training and documentation.
- Support existing AI solutions by refinement, troubleshooting, and reconfiguration
Scope of Work and Responsibilities:
AI Solution Development:
- Collaborate with cross-functional teams to identify AI opportunities.
- Train, validate, and optimize machine learning models.
- Translate business requirements to technical specifications.
AI Solution Implementation
- Develop code, deploy AI models and into production environments, and conduct ongoing model training
- Monitor performance and troubleshoot issues and engage in fine-tuning the solutions to improve accuracy
- Ensure compliance with ethical standards and data governance policies.
User Training and Adoption:
- Conduct training sessions for stakeholders on AI tools.
- Develop user guides and technical documentation.
Data Analysis and Research:
- Collect, preprocess, and engineer large datasets for machine learning and AI applications.
- Recommend and Implement Data Cleaning and Preparation
- Analyse and use structured and unstructured data (including geospatial data) to extract features and actionable insights.
- Monitor data quality, detect bias, and manage model/data drift in production environments.
- Research emerging AI technologies and recommend improvements.
Governance, Strategy, Support, and Maintenance:
- Advise client's staff on AI strategy and policy implications
- Contribute to the team s AI roadmap and innovation agenda.
- Provide continuous support and contribute towards maintenance and future enhancements.
Deliverables:
- Work on Proof of Concepts to study the technical feasibility of AI Use Cases
- Functional AI applications integrated into business systems.
- Documentation of model/application architecture, training data, and performance metrics.
- Training materials and user guides.
- Develop, train, and deploy AI models tailored to business needs
Mindlance is an Equal Opportunity Employer and does not discriminate in employment on the basis of Minority/Gender/Disability/Religion/LGBTQI/Age/Veterans.
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