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Machine Learning Engineer Jobs in Conway, AR (NOW HIRING)

AI Engineer

Little Rock, AR · On-site

$100K - $110K/yr

Design, develop, and deploy machine learning models and AI-driven applications * Collaborate with software engineers and product teams to integrate AI solutions into existing platforms * Analyze ...

... analytics engineering focus on leveraging advanced technologies and techniques to design and ... Those in artificial intelligence and machine learning at PwC will focus on developing and ...

Software Engineer Supervisor: Information Technology Director Employment Type: Full-Time FLSA ... Familiarity with machine learning (e.g., Python, TensorFlow, PyTorch, or scikit-learn) and interest ...

Software Engineer Supervisor: Information Technology Director Employment Type: Full-Time FLSA ... machine learning (e.g., Python, TensorFlow, PyTorch, or scikit-learn) and interest in future in ...

... s Full-Stack Engineer with expertise in IaC (Terraform), Helm, MySQL, Kubernetes, and CI/CD ... Experience with AI/machine learning technologies is strongly preferred. * Familiarity with TCP/IP ...

Data Science Tutor

Conway, AR · Remote

$18 - $40/hr

Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning, data visualization, SQL, Python or R programming, hypothesis testing, and communication of data ...

Python Tutor

Conway, AR · Remote

$18 - $40/hr

Emphasizes readable, maintainable code and connects Python to machine learning, web scraping, scientific computing, and DevOps applications. * Curriculum Awareness & Adaptive Instruction: Familiar ...

ERP AI Engineer - Manager

Little Rock, AR · On-site

$99K - $232K/yr

... Machine Learning. Enhancing your leadership style, you motivate, develop and inspire others to ... The Opportunity As part of the Data and Analytics Engineering team, you will serve as both a ...

Showing results 21-40

Machine Learning Engineer information

See Conway, AR salary details

$27.6K

$112.9K

$169.7K

How much do machine learning engineer jobs pay per year?

As of Aug 22, 2026, the average yearly pay for machine learning engineer in Conway, AR is $112,927.00, according to ZipRecruiter salary data. Most workers in this role earn between $89,000.00 and $135,900.00 per year, depending on experience, location, and employer.

What is a machine learning engineer?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

What does a machine learning engineer do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

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

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

What are some common challenges faced by machine learning engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

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

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate 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 Conway, AR?

The most popular types of Machine Learning Engineer jobs in Conway, AR are:

What are popular job titles related to Machine Learning Engineer jobs in Conway, AR?

For Machine Learning Engineer jobs in Conway, AR, the most frequently searched job titles are:

What cities near Conway, AR are hiring for Machine Learning Engineer jobs?

Cities near Conway, AR with the most Machine Learning Engineer job openings:

Infographic showing various Machine Learning Engineer job openings in Conway, AR as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 25% Part Time, and 1% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $112,927 per year, or $54.3 per hour.

Senior Data Scientist - Identity

LiveRamp

Little Rock, AR

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 20 days ago


Job description

LiveRamp is the data collaboration platform of choice for the world's most innovative companies. A groundbreaking leader in consumer privacy, data ethics, and foundational identity, LiveRamp is setting the new standard for building a connected customer view with unmatched clarity and context while protecting precious brand and consumer trust. LiveRamp offers complete flexibility to collaborate wherever data lives to support the widest range of data collaboration use cases-within organizations, between brands, and across its premier global network of top-quality partners.

Hundreds of global innovators, from iconic consumer brands and tech giants to banks, retailers, and healthcare leaders turn to LiveRamp to build enduring brand and business value by deepening customer engagement and loyalty, activating new partnerships, and maximizing the value of their first-party data while staying on the forefront of rapidly evolving compliance and privacy requirements.

You will:

  • Design, implement, and iterate on production-grade machine learning and statistical models that power core identity, entity resolution, and measurement capabilities.

  • Analyze and transform large-scale, high-dimensional, and often messy datasets to uncover actionable insights, engineer robust features, and improve model performance and stability.

  • Own end-to-end data science workflows-from problem framing, data exploration, and modeling through deployment, monitoring, and continuous improvement-in close collaboration with Engineering.

  • Translate complex technical concepts and analysis into clear recommendations and narratives for product, engineering, and go-to-market stakeholders to inform roadmaps and prioritization.

  • Define and track success metrics, build experimentation and evaluation frameworks, and tests to quantify the business impact of your work.

  • Partner with Product Management to scope data-driven solutions that address customer needs, validate hypotheses with data, and de-risk new product investments.

  • Contribute high-quality, well-tested, and maintainable code, documentation, and dashboards that make your work reproducible, observable, and easy to operate.

  • Mentor and support other data scientists and analysts through code reviews, design sessions, and sharing best practices.

Your team will:
  • Build and evolve data science capabilities that sit at the heart of LiveRamp's identity and data collaboration products, working closely with engineering teams across the company.

  • Tackle a diverse portfolio of problems, from improving core matching and graph-based algorithms to powering customer-facing features for targeting, measurement, and analytics.

  • Collaborate cross-functionally with product, engineering, customer success, and go-to-market teams to ship solutions that are technically sound, operationally scalable, and aligned with customer needs.

  • Maintain a culture of experimentation and scientific rigor, using well-designed tests, strong baselines, and clear metrics to guide decisions.

  • Invest in shared tooling, libraries, and best practices that raise the bar for how data science is done and operationalized across LiveRamp.

About you:
  • MS or PhD in Computer Science, Machine Learning, Statistics, Applied Mathematics, or a related quantitative field, or equivalent practical experience.

  • 3+ years of experience designing, building, and deploying data science or machine learning solutions in a production environment.

  • Proficiency in Python and SQL, along with experience using common data and ML libraries and frameworks (for example, pandas, NumPy, scikit-learn, or similar).

  • Experience working with large datasets in a cloud environment and with modern data processing frameworks or warehouses (for example, BigQuery).

  • Demonstrated ability to independently frame ambiguous business or product questions as concrete, testable data science problems.

  • Strong analytical and problem-solving skills, with a focus on clear measurement, experimentation, and data-informed decision-making.

  • Excellent written and verbal communication skills, including the ability to present complex technical topics to both technical and non-technical audiences.

  • A product-focused mindset and a strong bias toward iterative execution-you are comfortable moving from idea to prototype to production quickly while incorporating feedback.

Preferred Skills:
  • Experience with embeddings, representation learning, or large-scale similarity and ranking systems.

  • Experience with approximate nearest neighbor search, vector databases, or other large-scale vector search technologies.

  • Experience designing and implementing robust evaluation frameworks and monitoring for ML systems, including offline/online metric alignment and experimentation.

  • Experience with Google Cloud Platform and its data and ML ecosystem (for example, BigQuery, Dataflow, Vertex AI, or similar).

  • Familiarity with privacy-preserving data practices and governance, and interest in responsible and ethical use of data.

  • Experience with identity, entity resolution, or graph-based modeling in advertising, marketing, or adjacent domains.
    The approximate annual base compensation range is $130,000 to $196,500. The actual offer, reflecting the total compensation package and benefits, will be determined by a number of factors including the applicant's experience, knowledge, skills, and abilities, geography, as well as internal equity among our team.

Benefits:
  • People: Work with talented, collaborative, and friendly people who love what they do.
  • Fun: We host in-person and virtual events such as game nights, happy hours, camping trips, and sports leagues.
  • Work/Life Harmony: Flexible paid time off, paid holidays, options for working from home, and paid parental leave.
  • Comprehensive Benefits Package: LiveRamp offers a comprehensive benefits package designed to help you be your best self in your personal and professional lives. Our benefits package offers medical, dental, vision, life and disability, an employee assistance program, voluntary benefits as well as perks programs for your healthy lifestyle, career growth and more.
  • Savings: Our 401K matching plan-1:1 match up to 6% of salary-helps you plan ahead.

More about us:
LiveRamp's mission is to connect data in ways that matter, and doing so starts with our people. We know that inspired teams enlist people from a blend of backgrounds and experiences. And we know that individuals do their best when they not only bring their full selves to work but feel like they truly belong. Connecting LiveRampers to new ideas and one another is one of our guiding principles-one that informs how we hire, train, and grow our global team across nine countries and four continents. Click here to learn more about Diversity, Inclusion, & Belonging (DIB) at LiveRamp.

LiveRamp is an affirmative action and equal opportunity employer (AA/EOE/W/M/Vet/Disabled) and does not discriminate in recruiting, hiring, training, promotion or other employment of associates or the awarding of subcontracts because of a person's race, color, sex, age, religion, national origin, protected veteran, disability, sexual orientation, gender identity, genetics or other protected status. Qualified applicants with arrest and conviction records will be considered for the position in accordance with the San Francisco Fair Chance Ordinance.


We use automated decision systems (ADS) as part of our recruitment and hiring process. If you require an accommodation or believe that the use of an ADS may create a barrier to your application or participation in the hiring process due to a disability or other protected characteristic, please let us know. We are committed to providing reasonable accommodations and ensuring an equitable hiring experience for all candidates.


California residents: Please see our California Personnel Privacy Policy for more information regarding how we collect, use, and disclose the personal information you provide during the job application process.


To all recruitment agencies: LiveRamp does not accept agency resumes. Please do not forward resumes to our jobs alias, LiveRamp employees or any other company location. LiveRamp is not responsible for any fees related to unsolicited resumes.