Who We Are
Arrive Logistics is a leading transportation and technology company in North America with plans to grow significantly year over year. Our success is a testament to our remarkable team and what we’re building together. We’re committed to providing employees with a meaningful work experience and have established an award-winning culture that supports personal and career development in a fun, casual, and collaborative environment.
Who We Want
The Data Scientist II will work closely with Data Science, Product, and Engineering to build and improve ML and AI systems that drive operational value. This role is a great fit for a hands-on practitioner with applied experience in NLP and LLM-based systems who is ready to take on meaningful technical ownership. You'll contribute to the full lifecycle of production ML systems — from evaluation and measurement through development, deployment, and iteration — with a particular focus on text and language-based applications. The ideal candidate is comfortable operating in ambiguous problem spaces, can translate loosely defined business needs into concrete technical approaches, and communicates findings clearly to both technical and non-technical audiences.
What You'll Do
- Develop, evaluate, and iterate on NLP and LLM-based systems, including text classification, information extraction, and context retrieval pipelines.
- Build measurement and evaluation frameworks — both offline and online — to assess where and why systems are underperforming and quantify the impact of improvements.
- Develop golden test datasets and define methodologies for creating and maintaining them over time, including designing annotation guidelines and ensuring label quality.
- Evaluate and apply the appropriate approach for language tasks — whether prompt engineering, fine-tuning, or classical NLP methods — including modern retrieval and RAG architectures and LLM evaluation methodologies, based on the problem and available data.
- Perform structured analysis of system performance to surface failure modes, data gaps, and high-value areas for investment, applying sound statistical reasoning to evaluation results.
- Partner with engineers to support deployment, integration, and monitoring of ML and AI systems in production.
- Contribute to standards and best practices around deploying, evaluating, and monitoring text and language-based ML systems.
- Document work clearly and maintain knowledge artifacts that make systems understandable and maintainable over time.
- Collaborate with senior data scientists and cross-functional partners to translate business needs into well-scoped technical solutions, including communicating findings and recommendations to non-technical stakeholders.
Qualifications
- Bachelor's or Master's degree in a quantitative field (computer science, statistics, linguistics, or related) and 2–4 years of applied ML or data science experience, or equivalent practical experience.
- Hands-on experience building or improving NLP or LLM-based systems in applied settings.
- Familiarity with text classification, information extraction, or other NLP tasks — and an understanding of where these systems fail.
- Experience with both prompt engineering and fine-tuning approaches for language tasks, with the judgment to know when to apply each.
- Familiarity with modern retrieval strategies and RAG architectures and how they affect LLM system performance.
- Experience with Hugging Face Transformers for text classification or related NLP tasks.
- Experience contributing to evaluation frameworks, test sets, or performance diagnostics for ML systems, including comfort with statistical methods for measuring model performance.
- Proficiency in Python and SQL, and comfort working with structured and unstructured data.
- Ability to operate effectively in ambiguous problem spaces — scoping technical approaches when requirements are not fully defined.
- Strong written communication skills; able to document systems and findings clearly and present recommendations to non-technical stakeholders.
- Experience designing data annotation workflows, labeling guidelines, or label quality processes is a plus.
- Experience with model deployment, monitoring, or production ML workflows is a plus.
- Familiarity with LangChain and LangSmith or similar LLM orchestration and observability tooling is a plus.
- Transportation or logistics industry experience is a plus.
The Perks of Working With Us
- Take advantage of our comprehensive benefits package, including medical, dental, vision, life, disability, and supplemental coverage.
- Invest in your future with our matching 401(k) program.
- Build relationships and find your home at Arrive through our Employee Resource Groups.
- Enjoy office wide engagement activities, team events, happy hours and more!
- Leave the suit and tie at home; our dress code is casual.
- Work in the booming city of Austin, TX – we are in a convenient location close to the airport and downtown.
- Park your car for free on site!
- Start your morning with a specialty drink from our fully stocked coffee bar, Broker’s Brew.
- Sweat it out with the team at our onsite gym.
- Maximize your wellness with free counseling sessions through our Employee Assistance Program
- Take time to manage your physical and mental health - we offer company paid holidays, paid vacation time and wellness days.
- Receive 100% paid parental leave when you become a new parent.
- Get paid to work with your friends through our Referral Program!
- Get relocation assistance! If you are not local to the area, we offer relocation packages.
Skills Required
- Bachelor's or Master's degree in a quantitative field (computer science, statistics, linguistics, or related) or equivalent practical experience with 2-4 years applied ML or data science experience
- Hands-on experience building or improving NLP or LLM-based systems in applied settings
- Familiarity with text classification, information extraction, or other NLP tasks and understanding of failure modes
- Experience with prompt engineering and fine-tuning approaches for language tasks
- Familiarity with modern retrieval strategies and RAG architectures
- Experience with Hugging Face Transformers for text classification or related NLP tasks
- Experience contributing to evaluation frameworks, test sets, or performance diagnostics for ML systems, including statistical methods
- Proficiency in Python and SQL
- Ability to operate effectively in ambiguous problem spaces and scope technical approaches
- Strong written communication skills and ability to present findings to non-technical stakeholders
- Experience designing data annotation workflows, labeling guidelines, or label quality processes
- Experience with model deployment, monitoring, or production ML workflows
- Familiarity with LangChain and LangSmith or similar LLM orchestration and observability tooling
- Transportation or logistics industry experience
Arrive Logistics Compensation & Benefits Highlights
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Healthcare Strength — Company materials highlight medical, dental, vision, life, and disability coverage, complemented by EAP and telehealth options. Wellness apps and programs are also cited as part of the health ecosystem.
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Parental & Family Support — Paid parental leave, a post‑leave return program, onsite Mothers’ Rooms, and family medical leave are publicly described as part of the package. These elements indicate a family‑supportive approach beyond baseline benefits.
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Wellbeing & Lifestyle Benefits — Wellness tools such as Calm and Sanvello, fitness discounts/ClassPass, gym access where available, and onsite amenities are repeatedly listed. These lifestyle perks broaden total rewards beyond core insurance and retirement.
Arrive Logistics Insights
What We Do
Arrive Logistics is a top 4 American truckload brokerage headquartered in Austin, Texas, with 10 locations across North America. Founded in 2014, Arrive delivers unparalleled service and custom strategic solutions to a diverse network of globally recognized brands and vetted carriers. Arrive has 2,000 employees, 5,500 customers, and 10,000 core carriers in its network. The Company has been recognized for its service excellence by more than 50 enterprise shippers in the trailing 36 months. At Arrive, 'We Deliver, So You Can.“ For more information, visit www.arrivelogistics.com.
Why Work With Us
We are an ambitious, high-growth company that pushes the limit of what’s possible for our team and partners. In only 10 years, Arrive surpassed 30,000 competitors to become a Top 7 truckload brokerage — and we’re just getting started. We are on track to break into the Top 5 by 2025 and the Top 3 by 2026.
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