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Artificial Intelligence/Machine Learning Engineer II
Overall Exp: Minimum 15+ Years
Location : Austin Texas
• Total Hours: 2080
• Service Term Expected: 12-month duration
•Work hours and Location: 8AM – 5PM, 6230 E Stassney Ln, Austin, TX 78744
This position requires candidates to be onsite 5 days a week. Candidates must be LOCAL.
NOTE : Previous State Project Experience is Not Required
As part of the AI Technical Team, you will design, build, and deploy advanced models and AI solutions to solve real-world problems. You will work with large datasets, AI frameworks, and cross-functional teams to deliver impactful results that align with our business goals.
Minimum Yrs of Experience, Skills, and Qualifications
- 4-7 years: Experience creating end-to-end custom applications leveraging AI technologies
- 4-7 years: Designing and implementing RAG solutions using vector databases, embedding models, scripting, and LLMs to enhance contextual relevance and accuracy in generative outputs.
- 4-7 years: Experience and judgement for designing cutting edge technology solutions
- 4-7 years: Evaluating and benchmark generative models using quantitative and qualitative metrics to ensure performance, safety, accuracy, and reliability.
- 4-7 years: Monitoring and improving model performance through continuous feedback loops, error analysis, and prompt engineering.
- 4-7 years: Contributing to ethical AI practices, including bias detection, content filtering, implementation of guardrails, and responsible deployment strategies.
- 1 year: Evaluate appropriate LLMs and associated model providers, the modality of accessing these models (SaaS/PaaS), data obfuscation strategies for interacting with models, and cost parameters
- 1 year: Determine appropriate architecture for AI services
- 1 year: Developing/maintaining AI Agents
- 1 year: Use of Azure AI Foundry services for building AI solutions
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SL No
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Skills / Experience
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Required Experience
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Candidate Experience
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1
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Experience creating end-to-end custom applications leveraging AI technologies
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4–7 years
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2
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Designing and implementing RAG solutions using vector databases, embedding models, scripting, and LLMs to enhance contextual relevance & accuracy
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4–7 years
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3
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Experience and judgment for designing cutting-edge technology solutions
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4–7 years
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4
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Evaluating and benchmarking generative models using quantitative & qualitative metrics (performance, safety, accuracy, reliability)
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4–7 years
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5
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Monitoring and improving model performance through continuous feedback loops, error analysis, and prompt engineering
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4–7 years
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6
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Contributing to ethical AI practices (bias detection, content filtering, guardrails, responsible deployment strategies)
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4–7 years
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7
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Evaluate appropriate LLMs, model providers, modalities (SaaS/PaaS), data obfuscation strategies, and cost parameters
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1 year
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8
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Determine appropriate architecture for AI services
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1 year
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9
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Developing / maintaining AI Agents
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1 year
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10
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Use of Azure AI Foundry services for building AI solutions
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1 year
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