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Software

Atlanta, US Remote Full-time $130,000 – $185,000

About Winixx

Winixx Inc. is a New York-based technology holding company operating a portfolio of over 30 SaaS platforms across freight, fleet management, financial infrastructure, and market intelligence. Founded with a mission to modernize fragmented and underserved industries, Winixx builds technology that removes inefficiencies, creates transparency, and puts more value in the hands of the people doing the actual work. Our flagship products include Winixx Freight, a next-generation load board with embedded instant payment; fleetOS, a comprehensive fleet management and roadside assistance platform; and Baron Meddy Financial, our financial infrastructure arm facilitating capital deployment, escrow, and M&A advisory across verticals. Winixx is headquartered in Atlanta, Georgia, with remote teams operating nationwide.

Role Summary

The Machine Learning Engineer at Winixx builds the models and data systems that power intelligent features across our platforms — from load matching optimization and dynamic pricing to predictive maintenance alerts and fraud detection. You will work at the intersection of data engineering and applied research, taking models from proof-of-concept to production.

What You'll Do

• Design, build, and deploy machine learning models that improve core platform outcomes including load matching, pricing, and fraud detection
• Collaborate with data engineers to build and maintain feature stores and training data pipelines
• Implement model monitoring and retraining pipelines to maintain model performance over time
• Work with product and engineering teams to integrate ML predictions into production systems
• Conduct experimentation to validate model improvements using rigorous A/B testing methodology
• Document model architectures, training procedures, and performance benchmarks
• Evaluate and adopt new ML tools, frameworks, and techniques relevant to logistics and marketplace problems
• Contribute to the development of Winixx's internal ML platform and infrastructure

What We're Looking For

• 3+ years of machine learning engineering or applied research experience
• Strong Python skills with proficiency in ML frameworks such as PyTorch, TensorFlow, or scikit-learn
• Experience building and maintaining end-to-end ML pipelines in a production environment
• Solid foundation in statistics, probability, and optimization
• Experience with recommendation systems, pricing models, or anomaly detection is highly valued
• Familiarity with MLOps practices including model versioning, monitoring, and deployment
• Strong SQL and data manipulation skills
• Bachelor's or Master's degree in Computer Science, Statistics, or a related quantitative field

• Competitive base salary commensurate with experience
• Performance bonus program tied to individual and company milestones
• Hybrid work environment with flexible scheduling
• Career growth opportunities across 30+ SaaS products and multiple verticals
• Front-row seat at a technology company at the beginning of a major national expansion
• Collaborative, mission-driven team environment
• Paid time off and company holidays
• Professional development and continuing education support

Winixx Inc. is an equal opportunity employer. We evaluate all applicants on the basis of qualifications, experience, and demonstrated ability without regard to race, color, religion, sex, national origin, disability, veteran status, or any other characteristic protected by applicable law.

The compensation range reflected in this posting represents the minimum and maximum target range for this position. Individual pay within the posted range is determined by a candidate's demonstrated experience, educational background, skill set, and geographic location. Final compensation is established at the time of offer and may fall anywhere within the stated range based on these factors.

Compensation ranges reflect national US market data and are subject to change. Additional forms of compensation may include performance bonuses, equity participation, and other benefits as outlined in your offer documentation.