
1001 - 5000 employees
Founded 1975
🚘 Automotive
🏭 Manufacturing
🛡️ Insurance
Automotive • Manufacturing • Insurance
Murphy-Hoffman Company (MHC Kenworth) is a full service dealership network specializing in the sale and servicing of heavy-duty and medium-duty trucks, predominantly featuring Kenworth and Volvo brands. With over 130 locations across 19 states, MHC offers a wide range of services including truck sales, leasing, financing, and repair services. Their commitment to customer service is supported by 24/7 operations in major markets and a robust inventory of trucks and parts.
🕒 September 21
Improve your chances of getting an interview by checking your resume score before you apply.

1001 - 5000 employees
Founded 1975
🚘 Automotive
🏭 Manufacturing
🛡️ Insurance
Automotive • Manufacturing • Insurance
Murphy-Hoffman Company (MHC Kenworth) is a full service dealership network specializing in the sale and servicing of heavy-duty and medium-duty trucks, predominantly featuring Kenworth and Volvo brands. With over 130 locations across 19 states, MHC offers a wide range of services including truck sales, leasing, financing, and repair services. Their commitment to customer service is supported by 24/7 operations in major markets and a robust inventory of trucks and parts.
• Architect and build MHC’s core data platform across ingestion, transformation, storage, and serving layers for batch and streaming workloads • Model data for analytics and product use cases, creating documented reusable datasets and a trusted semantic layer • Establish data quality, lineage, observability, governance, reliability, discoverability, and security practices • Build pipelines and feature/embedding stores for analytics, ML, and LLM applications • Turn operational and document data into metrics, signals, predictions, and document understanding capabilities • Build and evaluate models and retrieval systems, including RAG over documents • Partner with Product to design and ship LLM-powered features from prototype to production with guardrails, evaluation, and cost controls • Manage, mentor, and grow a team of 2–4 data and AI engineers • Set goals, provide feedback, and develop team careers • Set technical standards and a pragmatic data and AI roadmap • Make build-vs-buy decisions and balance delivery speed with maintainability • Collaborate with Product, Engineering, and business stakeholders • Review code and designs, prototype difficult problems, and uphold engineering quality • Deliver a prioritized roadmap and early data-layer wins within 90 days • Establish a reliable, documented data foundation and bring an initial AI/LLM feature to production or customer testing within six months • Lead delivery of ongoing data products and AI features with strong quality and governance
• Bachelor’s degree in Computer Science, Information Security, or a related field or equivalent years of experience • 7+ years building data and/or backend systems in production • Recent hands-on experience in both data engineering and applied AI/ML • Strong SQL and Python • Experience with a cloud warehouse/lakehouse such as Snowflake, BigQuery, Databricks, or Redshift • Experience with transformation tools such as dbt • Experience with orchestration tools such as Airflow, Dagster, or Prefect • Hands-on experience building production AI/ML features • Practical experience with LLMs, including prompting, RAG, embeddings/vector search, evaluation, and model API integration • Software engineering fundamentals including data modeling, API design, testing, CI/CD, and reliable systems on AWS, GCP, or Azure • Experience leading or mentoring engineers • Strong product sense and communication skills • Preferred: document AI/intelligent document processing or NLP experience • Preferred: operating LLMs in production, including evaluation/observability, prompt and cost optimization, fine-tuning, or agentic workflows • Preferred: B2B SaaS, document/process automation, fintech, or other data-heavy enterprise domain experience • Preferred: data privacy, security, and compliance familiarity, such as SOC 2 or GDPR • Preferred: streaming, infrastructure-as-code, and MLOps/LLMOps tooling experience • Must be based in the United States • Not eligible for visa sponsorship
• Flexible, work-where-you-live model • 401(k) plan with deferred and Roth options • Employer 401(k) match of 50% up to a maximum of 4.5% of gross pay • Comprehensive medical plans with co-pay or HSA coverage options • Dental and vision plans • Daycare and Medical FSA/HSA • $50,000 group term life insurance • Generous paid time off (PTO) policies • Employee Assistance Program (EAP) • Additional life insurance • Critical illness insurance • Accident, cancer, and hospital indemnity insurance • Legal/ID Shield • Pet insurance • Four weeks of paid paternity leave after one year of employment, with partial eligibility beginning at six months, where applicable • Twelve weeks of paid leave for the birth parent, eligibility rules apply
Apply Now🕒 September 21
Senior Manager leading mobile identity and phone intelligence data acquisition for LexisNexis Risk Solutions. Managing suppliers, contracts, governance, and cross-functional data onboarding.
🕒 September 21
Senior Manager acquiring phone intelligence and mobile identity data for LexisNexis Risk Solutions. Managing suppliers, partnerships, governance, and commercialization across the U.S. market.
🕒 September 19
Data Science Manager leading AI, machine learning, and analytics initiatives at Reachlocal, a USA TODAY subsidiary. Supervising data scientists and delivering predictive solutions for strategic business decisions.
🕒 September 19
Data Scientist building Databricks and Python machine-learning solutions for V4C’s healthcare and member-engagement initiatives. Improving master data quality across complex healthcare datasets.
🕒 September 18
Data Scientist at Netflix designing experiments and causal-inference frameworks for personalized messaging. Building scalable analytics, dashboards, and data solutions for global member communications.