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Weekday Machine Learning Research Scientist Jobs in Dallas, TX

Machine Learning Engineer

Addison, TX · On-site +1

$110K - $130K/yr

... Science, Operations Research, Mathematics, Statistics, Econometrics) Expertise in manipulating and analyzing large data (e.g. exploratory analysis, model fitting, and visualization) Proficient SQL ...

Lead research initiatives to explore cutting-edge machine learning techniques and methodologies ... Mentor junior data scientists and machine learning engineers, providing technical guidance and ...

D. in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Applied Mathematics, Statistics, or a related technical discipline. * 8+ years of experience in AI/ML research ...

Machine Learning Engineer

Frisco, TX · On-site

$140 - $190/hr

... products, translating research outcomes into measurable platform impact. This list of ... D. preferred) in Computer Science, Machine Learning, or a closely related field. * Extensive ...

Showing results 21-40

Weekday Machine Learning Research Scientist information

See Dallas, TX salary details

$50K

$128.7K

$172.1K

How much do weekday machine learning research scientist jobs pay per year?

As of Sep 4, 2026, the average yearly pay for weekday machine learning research scientist in Dallas, TX is $128,716.00, according to ZipRecruiter salary data. Most workers in this role earn between $106,300.00 and $171,100.00 per year, depending on experience, location, and employer.

What does a Weekday Machine Learning Research Scientist do?

A Weekday Machine Learning Research Scientist conducts research and develops new algorithms or models in the field of machine learning, typically during standard business days (Monday to Friday). Their work involves designing experiments, analyzing data, publishing findings, and collaborating with other scientists or engineers. They may focus on improving existing machine learning techniques or creating innovative solutions for real-world problems. This role often requires a strong background in mathematics, computer science, and statistics, as well as proficiency in programming languages like Python or R.

What are some common challenges faced by a Weekday Machine Learning Research Scientist, and how are they typically addressed within the team?

Weekday Machine Learning Research Scientists often encounter challenges such as managing large datasets, tuning complex models, and keeping up with rapidly evolving research. Collaboration is key—team members regularly hold meetings to share findings, brainstorm solutions, and review code. Access to robust computational resources and mentorship from senior researchers helps address technical obstacles, while a structured, weekday schedule allows for focused research and effective work-life balance.

What are the key skills and qualifications needed to thrive as a Weekday Machine Learning Research Scientist, and why are they important?

To thrive as a Weekday Machine Learning Research Scientist, you need a solid background in mathematics, statistics, programming (Python, R), and a relevant advanced degree such as a Master's or Ph.D. in computer science or a related field. Expertise with machine learning frameworks (like TensorFlow, PyTorch), data processing tools, and familiarity with cloud computing platforms are typically required. Strong analytical thinking, problem-solving abilities, and clear communication skills help you collaborate with teams and present complex findings effectively. These skills are crucial for developing innovative models, delivering impactful research, and ensuring successful implementation in real-world applications.

What is the difference between Weekday Machine Learning Research Scientist vs Weekend Machine Learning Research Scientist?

AspectWeekday Machine Learning Research ScientistWeekend Machine Learning Research Scientist
CredentialsMaster's or PhD in Computer Science, Data Science, or related fieldsSame as weekday role
Work EnvironmentTypically in office or research labs during standard hoursFlexible hours, often part-time or project-based
Employer & Industry UsageTech companies, research institutions, startupsFreelance projects, consulting firms, academic collaborations

The main difference between a Weekday Machine Learning Research Scientist and a Weekend Machine Learning Research Scientist lies in their work schedule and environment. Weekday roles usually involve full-time employment with structured hours, while weekend roles are often part-time or freelance, offering more flexibility. Both roles require similar credentials and are used across tech and research industries.

Machine Learning Engineer

Confie

Addison, TX • On-site, Remote

$110K - $130K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

This job post has expired today. Applications are no longer accepted.


Job description

Pay Range:
  • $110000 - $130000 / year

Our Perks & Benefits:_
  • Comprehensive benefits package including medical, dental, vision, and life insurance
  • Performance-based bonuses to reward your contributions*
  • Paid time off to recharge and maintain a healthy work-life balance
  • Flexible work options, including remote and hybrid opportunities, if eligible
  • Retirement Plan (401k) with company-matched contributions
  • Education Advancement, for employees and qualified dependents, via the Confie Enablement Scholarship Fund
  • Fitness Reimbursement - up to $15/month for gym memberships
  • Inclusive workplace through a strong commitment to Diversity, Equity, and Inclusion
  • Employee Assistance Program - confidential support for personal or professional challenges, at no cost
  • Extra Perks - optional plans for disability, hospital indemnity, health advocate program, universal life, critical illness, accident insurance, and even pet insurance

Purpose
Work under the guidance and supervision of the Director, Enterprise Architecture to build supervised and unsupervised Artificial Intelligence (AI)/Machine Learning (ML) models
Essential Duties & Responsibilities
Research, analyze, support, and implement machine learning solutions on the Snowflake Cloud data warehouse platform using the Snowpark framework
Develop novel solutions using knowledge of the latest artificial intelligence/machine learning/natural language processing techniques and rigorous statistical analysis
Utilize LLMs and Generative AI to provide software automation capability integrations
Build and operationalize Retrieval Augmented Generation (RAG) frameworks
Enhance, develop, and deploy production-level machine learning models and algorithms that will improve Confie's business outcome/customer experience
Perform data cleansing, analysis, and feature engineering using Python
Ability to work with multiple data sources and types (structured/semi-structured/unstructured)
Assess the effectiveness and accuracy of new data sources and execute data-wrangling techniques
Participate and support other teams, as needed, for all aspects of model development, including design, model implementation, validation, calibration, documentation, product implementation, monitoring, and reporting
Communicate technical results in a clear, concise, and effective manner with emphasis on data visualization techniques
Collaborate with Data Scientists, Data Engineers, and Data Architects on production systems and applications
Stay up-to-date with industry trends and advancements in artificial intelligence/machine learning
On call support
Qualifications and Education Requirements
Master's degree in a quantitative/applied field (Engineering, Computer Science, Data Science, Operations Research, Mathematics, Statistics, Econometrics)
Expertise in manipulating and analyzing large data (e.g. exploratory analysis, model fitting, and visualization)
Proficient SQL skills and experience working with large data sets (big data, IoT data)
Proficient with programming and modeling using Python
Knowledge of modeling in pre-training & fine tuning foundation LLM models
Knowledge of LangChain and sentence transformer frameworks
Knowledge of ChatGPT4 (or comparable models)
Experience applying current machine learning techniques
Knowledge of evolving data science concepts and best practices
Other Duties
This job description is not designed to cover or contain a comprehensive listing of activities, duties, or responsibilities that are required of the employee for this job. Duties, responsibilities, and activities may change at any time with or without notice.
Notice
As permitted by applicable law and from time-to-time, Confie may use a computer system that has elements of artificial intelligence to help make decisions about your employment, including recruitment, hiring, renewal of employment, or the terms and conditions of your employment. Employees with questions about Confie's use of these computer systems should contact Human Resources at talent@confie.com
Equal Opportunity Employer
This employer is required to notify all applicants of their rights pursuant to federal employment laws.
For further information, please review the Know Your Rights notice from the Department of Labor.

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About Confie

Sourced by ZipRecruiter

Industry

Insurance services

Company size

1,001 - 5,000 Employees

Headquarters location

Huntington Beach, CA, US

Year founded

2008