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Senior Machine Learning Engineer Jobs in Frisco, TX

Tiger Analytics is looking for experienced Machine Learning Engineer with Gen AI experience to join our fast-growing advanced analytics consulting firm. Our employees bring deep expertise in Machine ...

Tiger Analytics is looking for experienced Machine Learning Engineer with Gen AI experience to join our fast-growing advanced analytics consulting firm. Our employees bring deep expertise in Machine ...

Machine Learning Engineer

Plano, TX ยท On-site

$120 - $150/hr

Overview Tiger Analytics is looking for experienced Machine Learning Engineer with Gen AI experience to join our fast-growing advanced analytics consulting firm. Our employees bring deep expertise in ...

Tiger Analytics is looking for experienced Machine Learning Engineer with Gen AI experience to join our fast-growing advanced analytics consulting firm. Our employees bring deep expertise in Machine ...

Lead Machine Learning Engineer

Plano, TX ยท On-site

$98K - $129K/yr

Lead Machine Learning Engineer As a Capital One Lead Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing Generative AI and advanced agentic systems at scale.

Lead Machine Learning Engineer

Plano, TX

$98K - $130K/yr

Lead Machine Learning Engineer As a Capital One Lead Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing Generative AI and advanced agentic systems at scale.

Lead Machine Learning Engineer

Plano, TX ยท On-site

$98K - $129K/yr

Lead Machine Learning Engineer As a Capital One Lead Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing Generative AI and advanced agentic systems at scale.

Manager, Machine Learning Engineer

Dallas, TX ยท On-site

$101K - $133K/yr

Leads a team of Machine Learning Engineers responsible for designing, building, deploying, and ... senior technology and business leaders. * Participates in special projects and performs other ...

... the machine learning function at a market-leading insurance company. As one of the first data ... Leverage continuous engineering practices to deliver business value regarding effectiveness of the ...

Machine Learning Engineer - NJ

Addison, TX ยท On-site

$54 - $71.50/hr

We are seeking a Machine Learning Engineer to design and develop robust analytics models using statistical and machine learning algorithms. In this role, you will work closely with product and ...

* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...

Senior Software Engineer Job Type: Contractor (~15 hours/week) Location: Remote Job Summary We are ... Create reinforcement learning environments for software engineering tasks. * Design tasks involving ...

Showing results 41-60

Senior Machine Learning Engineer information

See Frisco, TX salary details

$56.1K

$119.3K

$172.9K

How much do senior machine learning engineer jobs pay per year?

As of Sep 6, 2026, the average yearly pay for senior machine learning engineer in Frisco, TX is $119,274.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $135,200.00 per year, depending on experience, location, and employer.

What does a senior machine learning engineer do?

A Senior Machine Learning Engineer designs, develops, and implements machine learning models to solve complex problems. They are responsible for selecting appropriate algorithms, preprocessing data, and optimizing model performance. Additionally, they collaborate with data scientists, software engineers, and product teams to integrate machine learning solutions into production systems. Senior engineers also mentor junior team members and contribute to setting technical direction for machine learning projects.

What are some common challenges senior machine learning engineers face when deploying models to production, and how can they be addressed?

Senior Machine Learning Engineers often encounter challenges related to model scalability, maintaining performance in real-world scenarios, and ensuring reliable integration with existing systems. Addressing these challenges typically involves thorough testing, implementing robust monitoring for model drift, and collaborating closely with DevOps and software engineering teams to streamline deployment pipelines. Staying updated on best practices in MLOps and adopting tools for automated deployment and monitoring can greatly improve the reliability and efficiency of production models.

What are the key skills and qualifications needed to thrive as a senior machine learning engineer, and why are they important?

To thrive as a Senior Machine Learning Engineer, you need advanced knowledge of machine learning algorithms, statistical modeling, and programming languages like Python or Java, typically supported by a degree in computer science or a related field. Experience with frameworks and tools such as TensorFlow, PyTorch, scikit-learn, and cloud platforms, as well as familiarity with version control and CI/CD systems, is essential. Strong problem-solving, communication, and leadership skills help you collaborate effectively and mentor junior team members. These capabilities are crucial for designing scalable ML solutions and driving impactful results within complex, dynamic projects.

What is the difference between Senior Machine Learning Engineer vs Data Scientist?

AspectSenior Machine Learning EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, ML, or related; experience with ML frameworksBachelor's/Master's in CS, Statistics, or related; strong analytical skills
Work EnvironmentDevelops and deploys ML models in production systemsAnalyzes data, builds models, and provides insights
Industry UsageTech, finance, healthcare, e-commerceResearch, finance, marketing, tech

While both roles require strong technical skills and knowledge of machine learning, Senior Machine Learning Engineers focus more on deploying scalable ML solutions in production environments, whereas Data Scientists primarily analyze data and develop models for insights. The roles often overlap but differ in their core responsibilities and focus areas.

What are the most commonly searched types of Machine Learning Engineer jobs in Frisco, TX?

The most popular types of Machine Learning Engineer jobs in Frisco, TX are:

What are popular job titles related to Senior Machine Learning Engineer jobs in Frisco, TX?

For Senior Machine Learning Engineer jobs in Frisco, TX, the most frequently searched job titles are:

What job categories do people searching Senior Machine Learning Engineer jobs in Frisco, TX look for?

The top searched job categories for Senior Machine Learning Engineer jobs in Frisco, TX are:

What cities near Frisco, TX are hiring for Senior Machine Learning Engineer jobs?

Cities near Frisco, TX with the most Senior Machine Learning Engineer job openings:

Infographic showing various Senior Machine Learning Engineer job openings in Frisco, TX as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 25% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $119,274 per year, or $57.3 per hour.

Machine Learning Engineer

Tiger Analytics Inc.

Plano, TX โ€ข On-site

Full-time

Re-posted 25 days ago


Job description

Tiger Analytics is looking for experienced Machine Learning Engineer with Gen AI experience to join our fast-growing advanced analytics consulting firm. Our employees bring deep expertise in Machine Learning, Data Science, and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner.

Requirements


We are looking for an experiencedย AI/ML Leadย with deep expertise in designing and deploying high-performance APIs and microservices onย AWS Fargate (ECS). The ideal candidate will have hands-on experience inย generative AI integration,ย LLM API development, andย AWS Bedrock services, contributing to building scalable GenAI and Agentic AI applications.

Key Responsibilities:
  • Design, build, and optimize high-performanceย APIs and microservicesย usingย Python (Fast API)ย deployed onย AWS Fargate (ECS).
  • Integrateย LLM and Generative AI APIsย using providers such asย AWS Bedrock,ย OpenAI, and others.
  • Collaborate with ML and DevOps teams to designย CI/CD and MLOps pipelinesย within theย AWS ecosystem.
  • Contribute to architectural decisions around scalability, latency management, and backend efficiency for AI-powered systems.
  • (Preferred) Leverage familiarity withย Bedrock Agent Coreย services to integrate intelligent agent capabilities.
  • Develop and maintainย JSON RESTful APIs, adhering toย OpenAI APIย conventions and best practices.
Required Skills & Experience:
  • 5+ years of hands-on software development experience withย Python.
  • Proven expertise inย FastAPIย andย microservice architecture.
  • Strong understanding ofย cloud-native applications,ย container orchestration (ECS, Docker), and AWS tools.
  • Proficiency inย LLM API integrationย and working withย Generative AI frameworks.
  • Experience implementing CI/CD, IaC, and ML pipelines across AWS environments.
  • Familiarity withย Bedrock AgentCoreย or other agentic systems (nice to have).
Why Join Us:

You'll be part of an innovative team building the next generation ofย AI-driven applications, where scalability, performance, and intelligent automation converge. This is an opportunity to push boundaries inย Agentic AIย infrastructure development in a supportive, fast-moving environment.

Benefits

Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, fast-growing, challenging and entrepreneurial environment, with a high degree of individual responsibility.

Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.