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Apprentice Machine Learning Testing Jobs in Kyle, TX

Lead Machine Learning Engineer

Austin, TX · On-site

$255K - $280K/yr

As a Lead Machine Learning Engineer, you'll take ownership of complex, ambiguous problem spaces and ... Drive experimentation strategy, including A/B testing and offline evaluation, to continuously ...

Lead Machine Learning Engineer

Austin, TX · On-site

$255K - $280K/yr

As a Lead Machine Learning Engineer, you'll take ownership of complex, ambiguous problem spaces and ... Drive experimentation strategy, including A/B testing and offline evaluation, to continuously ...

Our team needs a Senior Consultant level Machine Learning Engineer with proven knowledge of web ... You should have strong problem-solving abilities and be passionate about coding, testing and ...

Tech Lead Machine Learning Engineer - Finance

Austin, TX · On-site

$101.60K - $133.80K/yr

As a machine learning engineer in Finance, you'll play an integral role in building the data ... testing standards, version control, and code reviews. Experience with front end (.js experience ...

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Apprentice Machine Learning Testing information

See Kyle, TX salary details

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How much do apprentice machine learning testing jobs pay per hour?

As of May 30, 2026, the average hourly pay for apprentice machine learning testing in Kyle, TX is $18.58, according to ZipRecruiter salary data. Most workers in this role earn between $15.67 and $20.29 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Apprentice Machine Learning Testing, and why are they important?

To thrive as an Apprentice in Machine Learning Testing, a foundational understanding of statistics, programming (especially Python), and basic machine learning concepts is essential, often supported by a degree or coursework in computer science or a related field. Familiarity with tools such as TensorFlow, PyTorch, Jupyter Notebooks, and version control systems is typically required. Strong analytical thinking, attention to detail, and effective communication skills help apprentices collaborate and identify testing issues efficiently. These skills ensure accurate model validation, effective troubleshooting, and contribute to the robust deployment of machine learning solutions.

What kinds of projects or tasks can I expect to work on as an Apprentice Machine Learning Testing?

As an Apprentice Machine Learning Testing, you’ll typically assist in evaluating machine learning models by designing and running tests, analyzing model outputs, and helping identify issues like bias or overfitting. You may work closely with data scientists and software engineers to validate model performance and ensure results align with project objectives. Your daily tasks might include preparing test datasets, executing automated testing scripts, and documenting findings to help improve model reliability. This role often serves as a valuable introduction to practical machine learning workflows and quality assurance processes in technical teams.

What does an Apprentice Machine Learning Testing do?

An Apprentice Machine Learning Testing professional assists in evaluating and validating machine learning models to ensure they perform as expected. They typically work under the guidance of experienced data scientists or engineers, running tests, analyzing results, and helping to identify issues such as bias or inaccuracies in algorithms. Their responsibilities may also include developing test cases, writing reports, and learning about data preprocessing and evaluation metrics. This role is ideal for those who are new to the field and want to build foundational skills in machine learning quality assurance.

What is the difference between Apprentice Machine Learning Testing vs Machine Learning Engineer?

AspectApprentice Machine Learning TestingMachine Learning Engineer
Required CredentialsBasic understanding of ML concepts, often pursuing relevant certifications or degreesAdvanced degrees (BSc, MSc, PhD) in CS or related fields, with extensive experience
Work EnvironmentEntry-level, supervised testing environments, often in training programsFull-time, independent development and deployment of ML models in production
Employer & Industry UsageInternships, training programs, entry-level roles in tech companiesEstablished tech firms, startups, research institutions

Apprentice Machine Learning Testing roles focus on learning and assisting with testing ML models under supervision, while Machine Learning Engineers design, build, and deploy ML systems independently. The apprentice position is ideal for gaining foundational skills, whereas the engineer role requires advanced expertise and experience.

What are popular job titles related to Apprentice Machine Learning Testing jobs in Kyle, TX? For Apprentice Machine Learning Testing jobs in Kyle, TX, the most frequently searched job titles are:
What job categories do people searching Apprentice Machine Learning Testing jobs in Kyle, TX look for? The top searched job categories for Apprentice Machine Learning Testing jobs in Kyle, TX are:
What cities near Kyle, TX are hiring for Apprentice Machine Learning Testing jobs? Cities near Kyle, TX with the most Apprentice Machine Learning Testing job openings:
Lead Machine Learning Engineer

Lead Machine Learning Engineer

Bumble Inc.

Austin, TX • On-site

$255K - $280K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 21 days ago


Job description

Introduction to the role & team Bumble exists to create a world where all relationships are healthy and equitable, and our Machine Learning team plays a vital role in shaping how millions of people connect, build trust, and find belonging. In this role, you'll operate at the intersection of product innovation and technical excellence, delivering intelligent systems that elevate both user experience and safety.
As a Lead Machine Learning Engineer, you'll take ownership of complex, ambiguous problem spaces and drive end-to-end machine learning solutions that span modelling, systems, and product integration. You'll champion our values of Courage and Excellence by making thoughtful technical decisions, challenging assumptions, and pushing for better outcomes.
AI is foundational to our future. You'll not only build high-impact ML systems, but also embed best practices in how AI is applied across the team, helping others adopt scalable, responsible, and effective approaches.
What You'll do
  • Lead the design and delivery of end-to-end ML systems powering recommendations, ranking, and personalization, driving measurable improvements in user outcomes
  • >
  • Architect and optimise ML pipelines, integrating data processing, model training, evaluation, and deployment into scalable systems (e.g. Spark, Airflow)
  • >
  • Build and deploy advanced models using modern frameworks (e.g. PyTorch), ensuring robustness in high-scale production environments
  • >
  • Develop and apply LLM-based capabilities, including prompt design and fine-tuning approaches for production use cases
  • >
  • Drive experimentation strategy, including A/B testing and offline evaluation, to continuously improve performance and inform product decisions
  • >
  • Partner cross-functionally with Product, Engineering, and Data teams, collaborating with purpose to translate business challenges into ML solutions
  • >
  • Mentor and support other engineers, fostering a culture of Curiosity, ownership, and continuous improvement
  • >

About You
  • Typically requires 7-10 years of experience, though we welcome candidates with alternative backgrounds that demonstrate equivalent skills.
  • >
  • Strong expertise in machine learning, with a track record of delivering end-to-end systems in production
  • >
  • Proficiency in Python and ML frameworks (e.g. PyTorch, TensorFlow), with experience in areas such as recommendation systems, ranking, or NLP
  • >
  • Experience designing and scaling ML pipelines and data systems (e.g. Spark, Airflow, or similar technologies)
  • >
  • Hands-on experience with LLMs, including prompting, evaluation, and production integration
  • >
  • Demonstrated ability to take ownership of ambiguous problems and deliver impactful outcomes
  • >
  • Strong collaboration skills, working cross-functionally and taking ownership of shared goals
  • >
  • Solid AI fluency, with the ability to guide best practices in model development and responsible AI usage within a team
  • >

$255,000 - $280,000 a year
For base compensation, we set standard ranges for all roles based on function, level, and geographic location. This position is also typically eligible to participate in our short- and long-term incentive programs. Benefits include Medical, Dental, Vision, 401(k) match, Unlimited Paid Time Off Policy.
Maven Fertility: $10,000 lifetime benefit for fertility, adoption, abortion care, and more.
26 Weeks Parental Leave: For both primary and secondary caregivers.
Family & Compassionate Leave: Inclusive of domestic violence recovery.
Unlimited Paid Time Off: Take the time you need.
Company-wide Week Off: Annual collective rest for the entire company.
Focus Fridays: No meetings, emails, or deadlines-just deep work.
About Us
Bumble Inc. is the parent company of Bumble Date, BFF, and Badoo. The Bumble platform enables people to build healthy and equitable relationships, through Kind Connections. Founded by Whitney Wolfe Herd in 2014, Bumble was one of the first dating apps built with women at the center and connects people across dating (Bumble Date) and friendship (BFF). BFF is a friendship app where people in all stages of life can meet people nearby and create meaningful platonic connections and community based on shared interests. Badoo, which was founded in 2006, is one of the pioneers of web and mobile dating products.
AI Fluency
AI is important to us. We're excited by people who are curious and experimental, and who think thoughtfully about how AI can amplify their impact and outcomes.
We encourage you to use AI responsibly as you prepare your application. Please don't use it to fabricate experiences or answer questions live in interviews. We care deeply about authenticity and want to understand your real skills, judgment and voice, because building a meaningful, genuine connection with you matters to us.
Final Compensation
Will be determined based on factors such as the selected candidate's qualifications, relevant experience, skill set, and other job-related considerations.
Benefits & Perks
Insurance: Medical/dental/vision, 30-day eligibility. Bumble has multiple competitive offerings that will be available to you on the first of the month following date of hire.
Unlimited PTO + 1 company-wide week off + Focus Fridays every week
Fully paid life and long-term disability insurance
401k with 4% company match if you contribute 6%, 90-day eligibility
Monthly wellness benefit and access to Noom, Unmind, and Your Money Line
Maternity and Fertility benefit + 26 week paid parental leave
Premium App Access
Inclusion at Bumble Inc.
Bumble Inc. is an equal opportunity employer and we strongly encourage people of all ages, colour, lesbian, gay, bisexual, transgender, queer and non-binary people, veterans, parents, people with disabilities, and neurodivergent people to apply. We're happy to make any reasonable adjustments that will help you feel more confident throughout the process, please don't hesitate to let us know how we can help.
In your application, please feel free to note which pronouns you use (For example: she/her, he/him, they/them, etc).
AI in Bumble Inc. Hiring
At Bumble, we may use AI tools to support parts of our recruitment process - such as helping us record, transcribe, and summarize conversations, and supporting job alignment by comparing resumes and job descriptions to highlight skills and potential roles that may be a good match. These tools help us work more efficiently and stay focused on you during our conversations. Importantly, all hiring decisions are made by people. AI is used only to support our team's efficiency and improve the candidate experience - not to evaluate or decide on your candidacy. Participation in AI-supported interviews and conversations is completely voluntary and will not impact your candidacy. If you'd prefer to opt out, simply let your recruiter or interviewer know at the start of a call, or anytime during the interview or conversation. Summaries and related data are retained only as long as needed in line with our internal data retention policies. If at any point you'd like a transcription or summary deleted, please contact your recruiter directly.
For further information on how we hold and manage your data, please refer to our Privacy Policy.