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Machine Learning Engineer Python Jobs in Lewisville, TX

Cisco

Principal Machine Learning Engineer

Dallas, TX · On-site

The Principal Machine Learning Engineer will define the vision for AI across platforms, lead the ... in Python and deep learning frameworks (e.g., PyTorch, TensorFlow) • Experience translating ...

AppFolio

Sr. Machine Learning Engineer

Richardson, TX

$94.30K - $129.50K/yr

Who We Are Looking For We're hiring a Senior Machine Learning Engineer to design and ship the next ... Expert Python, async programming, and WebSockets for real-time, bidirectional streaming. * ML ...

AppFolio

Sr. Machine Learning Engineer

Richardson, TX

$94.30K - $129.50K/yr

Who We Are Looking For We're hiring a Senior Machine Learning Engineer to design and ship the next ... Expert Python, async programming, and WebSockets for real-time, bidirectional streaming. * ML ...

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Machine Learning Engineer Python information

See Lewisville, TX salary details

$21.5K

$130.7K

$189.1K

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

As of Jun 4, 2026, the average yearly pay for machine learning engineer python in Lewisville, TX is $130,732.00, according to ZipRecruiter salary data. Most workers in this role earn between $103,200.00 and $153,600.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Machine Learning Engineer Python, and why are they important?

To thrive as a Machine Learning Engineer Python, you need a solid background in computer science, statistics, and mathematics, along with proficiency in Python programming and machine learning concepts. Familiarity with frameworks such as TensorFlow, PyTorch, Scikit-learn, and experience with cloud platforms or MLOps tools are highly valued, as are certifications like Google Professional Machine Learning Engineer. Strong problem-solving abilities, communication skills, and a collaborative mindset help set you apart in this field. These skills enable engineers to design, implement, and deploy effective machine learning solutions that address real-world challenges in dynamic, team-oriented environments.

What are some common challenges faced by Machine Learning Engineers working with Python, and how can they be addressed?

Machine Learning Engineers using Python often encounter challenges such as managing large datasets, ensuring efficient model deployment, and maintaining reproducibility of experiments. Handling data pipelines and model versioning can be complex, especially as projects scale. To address these issues, engineers typically use tools like Pandas and Dask for data handling, Docker for containerization, and MLflow or DVC for tracking experiments and models. Collaborating closely with data engineers, software developers, and product teams is also essential to streamline workflows and ensure models are production-ready.

What is a Machine Learning Engineer Python?

A Machine Learning Engineer Python is a professional who uses the Python programming language to design, build, and deploy machine learning models and systems. They work with large datasets, develop algorithms, and use Python libraries such as TensorFlow, scikit-learn, and PyTorch to solve complex problems. Their responsibilities also include preprocessing data, training models, evaluating performance, and integrating solutions into production environments. Machine Learning Engineers often collaborate with data scientists, software engineers, and business stakeholders to create scalable and efficient machine learning applications.

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

AspectMachine Learning Engineer PythonData Scientist
Required CredentialsBachelor's/Master's in CS, Data Science, or related; Python skills; ML certificationsBachelor's/Master's in Statistics, CS, or related; Python/R skills; Data analysis certifications
Work EnvironmentDevelops scalable ML models, deploys algorithms, collaborates with engineering teamsAnalyzes data, builds models, interprets results, communicates insights
Employer & Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research institutions

While both roles require Python proficiency and data skills, Machine Learning Engineers focus on building and deploying scalable ML models, whereas Data Scientists analyze data and generate insights. The roles often overlap but differ in their primary focus and responsibilities.

What job categories do people searching Machine Learning Engineer Python jobs in Lewisville, TX look for? The top searched job categories for Machine Learning Engineer Python jobs in Lewisville, TX are:
What cities near Lewisville, TX are hiring for Machine Learning Engineer Python jobs? Cities near Lewisville, TX with the most Machine Learning Engineer Python job openings:
Machine Learning Engineer Python jobs near you
Infographic showing various Machine Learning Engineer Python job openings in Lewisville, TX as of May 2026, with employment types broken down into 38% Full Time, 59% Part Time, and 3% Contract. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $130,732 per year, or $62.9 per hour.
Machine Learning Engineer, Specialist

Machine Learning Engineer, Specialist

Vangard, Inc.

Dallas, TX • On-site

$113.30K - $136K/yr

Full-time

Posted 13 days ago

Job description


Responsibilities:

  • Develops complex data pipelines and implements data engineering design principles for iterative data pipeline development to drive scale and efficiency. Proficient in model development environments and coding best practices to enable model deployment.

  • Integrates and optimizes existing data and model pipelines in a production environment. Identifies and diagnoses data inconsistencies and errors, documents assumptions, and forages to fill data gaps. Applies knowledge of experimental methodologies, statistics, optimization, probability theory, and machine learning concepts to create self-running artificial intelligence (AI) systems to automate predictive models. Proficient in SDLC processes and related tools and technologies.

  • Partners with data science teams to review model ready dataset document/feature documentation. Develops data model design and document and reviews for completeness with data science teams.

  • Partners with data science teams to understand data requirements, performs data discovery for model development. Performs detailed analysis of raw data sources for data quality, applies business context, and model development needs. Drives efficiency through the use of data discovery tools.

  • Engages with internal stakeholders to understand and probe business processes and develop hypotheses. Brings structure to requests and translates requirements into an analytic approach. Participates in and influences ongoing business planning and departmental prioritization activities.

  • Writes model monitoring scripts as needed. Diagnoses root causes based on model monitoring alerts and triages issues. Coordinates and plans response to model monitoring alerts and resolves issues.

  • Serves as a machine learning engineering subject matter expert on cross functional teams for large strategic initiatives and contributes to the growth of the Vanguard analytic community.

  • Participates in special projects and performs other duties as assigned.

  • Designs and implements statistical analysis frameworks and protocols to uncover business trends across functions like marketing, supply chain, and economics.

  • Applies advanced data mining techniques to build scalable models for deriving actionable insights from large-scale data sets.

  • Explores and integrates evolving methodologies in machine learning and big data science to enhance decision-making strategies.


Qualifications:

  • Minimum 8 years of experience in machine learning engineering or data science roles

  • Bachelor's degree (B.E./B.Tech) in Computer Science, Data Engineering, AI/ML, or related fields, or a Master's degree/Diploma in Computer Science or Data Science

  • Strong expertise in data pipeline development, statistical modeling, SDLC, AI/ML concepts, model monitoring, and stakeholder engagement across domains

Special Factors

Sponsorship

Vanguard is not offering visa sponsorship for this position.

About Vanguard

At Vanguard, we don't just have a mission-we're on a mission.

To work for the long-term financial wellbeing of our clients. To lead through product and services that transform our clients' lives. To learn and develop our skills as individuals and as a team. From Malvern to Melbourne, our mission drives us forward and inspires us to be our best.

How We Work

Vanguard has implemented a hybrid working model for the majority of our crew members, designed to capture the benefits of enhanced flexibility while enabling in-person learning, collaboration, and connection. We believe our mission-driven and highly collaborative culture is a critical enabler to support long-term client outcomes and enrich the employee experience.

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