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Senior Machine Learning Engineer Jobs in Spring, TX

Bespoke Labs

Machine Learning Engineer

Houston, TX · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Talentry, LLC

Be Seen First

Machine Learning Guru (Autonomous Navigation)**

Houston, TX · Remote

$200K - $300K/yr

Senior/Principal Machine Learning Engineer 200-300k Remote position possible Description * Develop solutions for autonomous driving, from experimentation to full commercialization. * Explore new ...

Cisco

Principal Machine Learning Engineer

Houston, TX · On-site

The Principal Machine Learning Engineer will define the vision for AI across platforms, lead the ... Cultivate organizational excellence by mentoring senior technical talent, fostering research ...

Cisco

Principal Machine Learning Engineer

Houston, TX

$291K - $369K/yr

Partner with executive leadership, engineering, product, and data science teams to ensure AI ... Cultivate organizational excellence by mentoring senior technical talent, fostering research ...

Pivotal Solutions

Senior AI Engineer

Houston, TX · On-site

$99K - $137K/yr

Design, develop, and deploy advanced AI and machine learning models to solve complex business ... Mentor junior engineers and provide technical guidance on AI best practices, model development, and ...

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All JobsSenior Machine Learning Engineer JobsSenior Machine Learning Engineer Jobs in Spring, TX

Senior Machine Learning Engineer information

See Spring, TX salary details

$54.8K

$116.5K

$169K

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

As of Jun 26, 2026, the average yearly pay for senior machine learning engineer in Spring, TX is $116,532.00, according to ZipRecruiter salary data. Most workers in this role earn between $96,200.00 and $132,100.00 per year, depending on experience, location, and employer.

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 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 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 Spring, TX? The most popular types of Machine Learning Engineer jobs in Spring, TX are:
What are popular job titles related to Senior Machine Learning Engineer jobs in Spring, TX? For Senior Machine Learning Engineer jobs in Spring, TX, the most frequently searched job titles are:
What job categories do people searching Senior Machine Learning Engineer jobs in Spring, TX look for? The top searched job categories for Senior Machine Learning Engineer jobs in Spring, TX are:
What cities near Spring, TX are hiring for Senior Machine Learning Engineer jobs? Cities near Spring, TX with the most Senior Machine Learning Engineer job openings:
Senior Machine Learning Engineer jobs near you
Infographic showing various Senior Machine Learning Engineer job openings in Spring, TX as of June 2026, with employment types broken down into 92% Full Time, 6% Part Time, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $116,532 per year, or $56 per hour.

Machine Learning Engineer

Bespoke Labs

The Woodlands, TX • On-site

Full-time

Posted 8 days ago

Job description

About Us

We are AI researchers and builders who understand how to curate data and RL environments that truly improve models. We curated OpenThoughts, one of the best open reasoning datasets, and have trained SOTA models such as Bespoke-MiniCheck and Bespoke-MiniChart.

We are embarked on a journey to build Environments that are entire digital worlds that can be used to push the frontier of agents.

What You'll Be Working On

You will work directly with our research team on RL environment and task creation for agent training. This means designing observation spaces, action spaces, reward signals, and success criteria for new environments — and building the infrastructure that makes world-scale RL training possible. This is a high-ownership role; you will be building novel systems, not maintaining legacy ones.

Must-Have Skills

3+ years of ML engineering experience — model training, fine-tuning, or post-training pipelines in research or production

Strong Python and deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed precision)

Hands-on experience with LLM post-training — SFT, RLHF, PPO, DPO, or reward model training — and understanding of how training data quality affects model behavior

Familiarity with RL frameworks (Gymnasium, dm_env) and the ability to design or modify reward functions for agent training objectives

Experience running experiments at scale on cloud or HPC (AWS, GCP, SLURM, or Ray)

Solid understanding of evaluation methodology — held-out sets, benchmark design, avoiding train/eval contamination

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