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IT Lead II ML Engineering
Job Location:
Job Location:
Frisco, TX - USA
Monthly Salary:
Not provided by the employer
Monthly Salary:
Posted:
13 June 2026 (30+ days ago)
Posted:
Application Deadline:
10 September 2026
Application Deadline:
Vacancies:
1 Vacancy
Vacancies:
Job Summary
Overview:
TekWissen is a global workforce management provider headquartered in Ann Arbor Michigan that offers strategic talent solutions to our clients world-wide. Our client provider of digital technology and transformation information technology and services
Position:Senior AI Consultant
Location: Frisco TX / Bellevue WA
Duration: 7 Months
Job Type: Temporary Assignment
Work Type:Onsite
Job Description:
About the Role:
- We are looking for a Senior AI Consultant to serve as a strategic advisor and technical architect for our AI transformation programme.
- The engagement spans multiple high-impact use cases in Telco Ops along with a broader model selection and cost-governance framework.
- You will play a thought leadership role guiding senior stakeholders on AI strategy architecture decisions and execution models-bringing both hands-on expertise in GenAI and traditional AI/ML as well as experience advising VP/Sr. Director-level leadership in large enterprises.
- You will help us make the right decisions on model architecture tooling implementation sequencing and team structure with a specific focus on when to use SLMs vs LLMs and how to build cost-efficient production-grade AI pipelines.
What You Will Do:
- Advise on architecture decisions for AI use cases involving SLM LLM hybrid AI pipelines across multiple AI tasks like classification information extraction document processing correlation and reasoning workloads.
- Review and challenge model selection choices benchmarking methodology and fine-tuning strategies for different AI tasks tasks
- Guide the cost-versus-accuracy trade-off analysis across model types (frontier LLM LLM with fine-tuning SLM instruct SLM fine-tuned) and workload profiles.
- Provide practical input on implementation approach team structure sprint sequencing and make-vs-buy decisions.
- Review data strategy labelling effort sizing evaluation harness design and MLOps requirements for each workload.
- Advise on how to structure the business case and design the appropriate AI architecture including executive-level cost latency and accuracy comparisons.
- Flag risks including vendor lock-in model drift data governance gaps and compliance requirements for use cases in regulated industries/domains
- Act as a trusted advisor to senior leadership (VP/Sr. Director level) shaping AI strategy and influencing key decision-making forums.
What You Must Have:
- 8 years of experience in applied ML and AI with at least 3 4 years in enterprise NLP or LLM/SLM system design and deployment.
- Demonstrable hands-on experience with SLMs including fine-tuning and deployment using models such as Phi Gemma Llama Mistral or Qwen families.
- Strong understanding of frontier LLM APIs (OpenAI Azure OpenAI Anthropic) and when they add genuine value over smaller models.
- Experience designing multi-task NLP pipelines covering classification named entity recognition document extraction RAG and reasoning.
- Ability to translate model architecture decisions into cost models and business cases (implementation cost run cost savings ROI).
- Experience with at least one of the following verticals: telecom healthcare or industrial/manufacturing B2B operations.
What is highly desirable:
- Experience with automation or workflow orchestration in high-volume operational environments.
- Knowledge of LLMOps practices for SLM deployment including quantization batching model versioning and latency benchmarking.
What success looks like in this role:
- Clear defensible architecture recommendation for each use case with rationale for model tier selection estimated implementation cost and projected run cost savings.
- A practical evaluation framework and scoring rubric that the internal team can use to benchmark models independently.
- A sequenced implementation roadmap that the delivery team can execute in 4-6 month phases.
- Executive-ready cost comparison across LLM-only SLM-only and hybrid approaches for each use case.
TekWissen Group is an equal opportunity employer supporting workforce diversity.
