Machine Learning Engineer Senior

Techstra Solutions; Dallas (TX); On-site; USD 130,000 - 190,000; Full time

Job summary

Techstra Solutions seeks a senior ML/GenAI engineer to lead development of cross-functional ML systems across platforms. You will design, build, and maintain advanced ML models while applying governance, risk management, and SDLC best practices to ensure production readiness.

You will collaborate with Data Scientists to refine prototypes, orchestrate model solutions, and support production deployments through release windows and ongoing governance.

Qualifications

• Production ML solutions leveraging generative AI and LLMs.
• Model governance and risk management
• SDLC practices to increase productivity and delivery speed

Responsibilities

• Develop cross-functional, multi-platform ML software systems.
• Design, build, and maintain ML models and pipelines.
• Collaborate with Data Scientists to refine prototypes and productionize models.
• Release planning and production support during releases.

Skills

Machine Learning

Customer Solutions

Risk Assessments

Technical Knowledge

Competitive Advantages

Enterprise Architecture

Tools

Azure Machine Learning

Azure AI Foundry

AWS SageMaker

Azure OpenAI

MLflow

Pinecone

Weaviate

pgvector

GitHub

Azure DevOps

Docker

CI/CD

Jira

Confluence

REST APIs

Microservices

Job description

Role Description:

Leads in the development of cross-functional, multi-platform machine learning software systems. Uses technical knowledge and industry experience to design, build and maintain technology solutions. Utilizes knowledge of advanced probability and statistics to create intricate machine learning algorithms. Applies complex higher level math concepts to build new models and validate existing models. Possesses Machine Learning industry expertise and stays current on best practices, hot topics, and emerging trends. Utilizes industry expertise to inform decisions and recommendations. Performs complex application programming activities including, coding, testing, debugging, documenting, maintaining, and modifying machine learning systems. Works with Data Scientist to understand prototype, and suggests modifications as necessary. Easily understands the bigger picture and possesses an enterprise-wide view. Skills: Machine Learning Customer Solutions Risk Assessments Technical Knowledge Competitive Advantages Design Enterprise Architecture Framework Experience: 5-7 years related experience.

• Experience implementing production solutions that leverage generative AI and LLMs, agentic frameworks
• Implementation/use of SDLC harnesses for increasing personal and team productivity
• Internal client consultation to elicit and collect requirements, and communicate and align the technical team toward delivery
• Model solution design, build, orchestration and implementation
• Experience building solutions with model governance, risk management, and regulatory adherence at top of mind
• Continuous support of models deployed to production applications
• Release planning, coordination, and hands on support throughout release windows

Machine Learning / GenAI

• Python, scikit-learn, PyTorch and/or TensorFlow
• Generative AI and Large Language Models (LLMs)
• Retrieval-Augmented Generation (RAG), embeddings, vector search
• Agentic AI frameworks such as LangChain, LangGraph, Semantic Kernel, or similar
• Model evaluation, validation, prompt engineering, and model monitoring
• Advanced probability, statistics, linear algebra, and optimization

AI/ML Platforms

• Azure Machine Learning, Azure AI Foundry, AWS SageMaker, or equivalent enterprise ML platforms
• Azure OpenAI/OpenAI APIs or comparable foundation-model platforms
• MLflow or similar experiment tracking/model lifecycle tooling
• Vector databases/search platforms such as Azure AI Search, Pinecone, Weaviate, or pgvector

Development & Engineering

• Git/GitHub or Azure DevOps
• REST APIs and microservices
• Docker and containerized deployments
• CI/CD pipelines and automated testing
• Jira/Confluence or similar Agile delivery tools
• SDLC practices, source control, code reviews, release management, and production support

Data

• SQL
• Data pipelines and data preparation
• Structured and unstructured data
• Feature engineering
• Data quality and validation
• API and enterprise data integration

Governance / Risk Knowledge

• Model governance and model risk management
• Responsible AI concepts
• Explainability, validation, bias/fairness, data privacy, and security
• Auditability and documentation
• Regulatory adherence and production controls

Equal Employment Opportunity Statement

Techstra Solutions is an equal opportunity employer. The Company makes its decisions on merit, and its policy of equal opportunity prohibits discrimination in all phases of the employment process, including, but not limited to, recruitment, hiring, promotion, selection, transfer, demotion, layoff, termination, compensation, benefits, and other terms and conditions of employment. The policy of equal opportunity applies without regard to race, color, creed, religion, gender, sexual orientation, gender identification, pregnancy, marital status, national origin, ancestry, age, disability that can reasonably be accommodated without undue hardship, military status, veteran status, genetic predisposition or carrier status, alienage or citizenship, domestic partnership status, arrest or conviction record, status as a victim of domestic violence, or any other protected categories under federal, state, or local law. The Company also prohibits discrimination or harassment based upon the perception that a person has, or is associated with a person who has, any of these characteristics.

Candidate Data Privacy and Use:

Techstra Solutions respects the privacy of our candidates. By submitting your application, you acknowledge that Techstra Solutions may collect, store, and process the information you provide for recruiting, candidate evaluation, and consideration for current or future opportunities. Techstra may use applicant tracking systems, analytics, automation, and AI-assisted tools to support these activities. Candidate information will be protected using appropriate safeguards and retained or deleted in accordance with applicable law and Techstra’s data retention practices.