1

Associate Machine Learning Jobs in Georgetown, TX

AI Solutions Architect

Austin, TX · On-site

$62.50 - $82.25/hr

... Machine Learning Engineer, Microsoft Azure AI Engineer Associate, Microsoft Azure Data Scientist Associate, or Microsoft Azure Solutions Architect Expert The wage range for this role takes into ...

As an Artificial Intelligence and Machine Learning Computational Science professional, you will ... Bachelor's degree or equivalent (minimum 12 years) work experience. (If Associate's Degree, must ...

Industry/Sector Not Applicable Specialism Oracle Management Level Senior Associate & Summary At PwC ... Responsibilities - Design and implement advanced AI and machine learning solutions - Analyze ...

New

Agentic DevOps Lead

Austin, TX · On-site

$70K - $205K/yr

You Are As an Artificial Intelligence and Machine Learning Computational Science professional, you ... Bachelor's degree or equivalent (minimum 12 years) work experience. (If Associate's Degree, must ...

next page

Showing results 1-20

Associate Machine Learning information

See Georgetown, TX salary details

$29.3K

$123.6K

$292.2K

How much do associate machine learning jobs pay per year?

As of Jun 19, 2026, the average yearly pay for associate machine learning in Georgetown, TX is $123,631.00, according to ZipRecruiter salary data. Most workers in this role earn between $42,700.00 and $187,700.00 per year, depending on experience, location, and employer.

What is the difference between Associate Machine Learning vs Data Scientist?

AspectAssociate Machine LearningData Scientist
Required CredentialsBachelor's degree in CS, Data Science, or related field; some roles may require certifications in ML or AIBachelor's or Master's in CS, Statistics, or related; often requires experience with data analysis and programming
Work EnvironmentEntry-level, team-based projects, focused on supporting ML models and data preprocessingMore autonomous, involved in data analysis, model development, and interpretation
Employer & Industry UsageTech companies, startups, research labs; roles in AI and ML teamsWide range of industries including tech, finance, healthcare, and consulting

While both roles involve working with data and machine learning, an Associate Machine Learning typically focuses on supporting ML projects with less experience, whereas a Data Scientist has broader responsibilities including data analysis, model development, and strategic insights. The roles often overlap but differ in scope and experience level.

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

To thrive as an Associate Machine Learning Engineer, you need a solid background in mathematics, programming (especially Python), and foundational machine learning concepts, usually supported by a relevant degree. Familiarity with tools like TensorFlow, PyTorch, scikit-learn, and experience with data processing libraries and version control systems is typically required. Strong analytical thinking, problem-solving ability, and effective collaboration skills help you stand out in this role. These competencies are essential for developing robust models, working efficiently with teams, and delivering impactful data-driven solutions.

What are some common challenges faced by Associate Machine Learning professionals when transitioning from academic projects to real-world business applications?

Associate Machine Learning professionals often find that moving from academic or theoretical projects to business-focused environments introduces new challenges. Real-world datasets can be messy, incomplete, or imbalanced, requiring additional data cleaning and preprocessing. Moreover, business timelines may require rapid prototyping and iterative model development, which is different from the more open-ended nature of academic research. Collaborating with cross-functional teams such as data engineers, product managers, and business stakeholders is also essential to align models with organizational goals. Adapting to these practical aspects is key to succeeding in an Associate Machine Learning role.

What does an Associate Machine Learning Engineer do?

An Associate Machine Learning Engineer assists in designing, developing, and deploying machine learning models under the supervision of senior engineers. They handle tasks such as data preprocessing, model evaluation, and maintaining machine learning pipelines. Associates often collaborate with data scientists, software engineers, and business teams to ensure that machine learning solutions are integrated effectively into products or services. This role is typically entry-level or early career and is a stepping stone toward more advanced machine learning positions.
What are the most commonly searched types of Machine Learning jobs in Georgetown, TX? The most popular types of Machine Learning jobs in Georgetown, TX are:
What cities near Georgetown, TX are hiring for Associate Machine Learning jobs? Cities near Georgetown, TX with the most Associate Machine Learning job openings:
Senior Lead Software Engineer - Data / Machine Learning Operations

Senior Lead Software Engineer - Data / Machine Learning Operations

Chase

Austin, TX

Other

Medical, Retirement

Posted 21 hours ago


JPMorgan Chase & Co. rating

8.1

Company rating: 8.1 out of 10

Based on 470 frontline employees who took The Breakroom Quiz

46th of 141 rated banks


Job description

Senior Lead Software Engineer

Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products.

As a Senior Lead Software Engineer at JPMorgan Chase within the Consumer and Community Banking - Risk Technology Portfolio team, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. Drive significant business impact through your capabilities and contributions, and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications.

Job Responsibilities

  • Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors
  • Develops secure and high-quality production code, and reviews and debugs code written by others
  • Design and develop large-scale solutions or platforms using Cloud services (i.e. AWS) in alignment with the firm wide strategies and security controls
  • Deploy and enable cloud based solutions at firm level, supporting complex analytics and day to day business operations
  • Migrate legacy and big data applications at Cloud native applications with zero downtime
  • Drives decisions that influence the product design, application functionality, and technical operations and processes
  • Develop solutions or tools to monitor, provision components for automation or the processes, services, and reports
  • Actively contributes to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software Development Life Cycle
  • Leverage your strong operational skills to develop impactful recommendations on upstream product, processes, or policy improvements that will optimize the user experience
  • Influences peers and project decision-makers to consider the use and application of leading-edge technologies
  • Adds to the team culture of diversity, opportunity, inclusion, and respect

Required Qualifications, Capabilities, and Skills

  • Formal training and certification on software engineering concepts and 5+ years applied experience. In addition, 2+ years of experience leading technologists to manage and solve complex technical items within your domain of expertise
  • Hands-on practical experience delivering system design, application development, testing, and operational stability
  • Good knowledge of Machine Learning modelling as an engineer
  • Advanced in one or more programming language(s) and framework(s) (i.e., Python, Java, Big Data, Data pipeline, Machine Learning, etc.)
  • Advanced knowledge of software applications and technical processes with considerable in-depth knowledge in one or more technical disciplines (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
  • Advanced knowledge of application, data, and infrastructure architecture disciplines
  • Working experience in software development, OOPS and SDLC
  • Ability to tackle design and functionality problems independently with little to no oversight
  • Knowledge of the financial services industry and their TI systems
  • Practical cloud native experience
  • Experience in Computer Science, Computer Engineering, Mathematics, or a related technical field

Preferred Qualifications, Capabilities, and Skills

  • AWS certifications (e.g. Solutions Architect Associate)
  • Knowledge of RAG architectures and exposure to AI/Automation technologies that improve operations
  • Experience with building Data Pipelines in Spark, Tuning Spark queries
  • Understands Python Machine Learning libraries and ecosystems (i.e., Pandas, Numpy, etc.)
  • Working knowledge with Big Data platforms (i.e., Hadoop preferred)
  • Experience in Cloud Technologies (i.e., AWS - Databricks preferred)
About Us

JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world's most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.

JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans

About the Team

Our Corporate Technology team relies on smart, driven people like you to develop applications and provide tech support for all our corporate functions across our network. Your efforts will touch lives all over the financial spectrum and across all our divisions: Global Finance, Corporate Treasury, Risk Management, Human Resources, Compliance, Legal, and within the Corporate Administrative Office. You'll be part of a team specifically built to meet and exceed our evolving technology needs, as well as our technology controls agenda.


What JPMorgan Chase & Co. employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom