Applied Industrial Technologies

5 months ago

Data & ML Pipeline Software Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 10 hours agoStatus: Live

Job Summary

Join Applied Intuition as a Data & ML Pipeline Software Engineer in the Self-Driving Systems team. You will build and maintain large-scale data processing pipelines, automate data selection and model training loops, and collaborate with ML engineers to improve training efficiency and deployment cycles for autonomous vehicle software. You will mentor engineers and shape data-centric development as vehicles learn from real-world and simulated data.

Location: Sunnyvale

Workplace: Onsite

Employment Type: Full time

Job Function: Software Engineering

Key Responsibilities

•Build and maintain large-scale data processing pipelines (ETL) for ingesting and curating driving datasets
•Design and implement systems that automate data selection, labeling, training, and testing loops
•Collaborate with modeling teams to improve training efficiency and model performance across iterations
•Develop the core infrastructure that closes the loop between real-world test results and new model deployments
•Mentor junior engineers and contribute to defining best practices for data-centric development

Pay and Benefits

Salary: USD 125,000 - 222,000 annually

Equity and Bonus:Equity

Perks:Health InsuranceDentalVision401kLearning StipendPaid Leave

Key Requirements

•Bachelor's or higher degree in Engineering such as Computer Science, Electrical Engineering, Software Engineering
•3–5 years of experience in software or data infrastructure engineering
•Expertise in building and scaling data pipelines, distributed systems, or ML infrastructure
•Proficiency in Python and strong knowledge of data frameworks (Spark, Airflow, Kafka, etc.)
•Experience working with large-scale datasets and understanding data-driven development cycles

Experience:3-5 yearsAutonomous systemsData engineeringMachine learningData pipelines

Education:Bachelor's

Skills:CommunicationProblem-solvingMentorship

Tech Stack:PythonSparkAirflowKafkaETLData pipelines

Company Brief

Applied Industrial Technologies

Applied Industrial Technologies is a distributor of industrial products and services, supplying bearings, power transmission, fluid power, safety products, and engineered solutions to maintenance, repair and operations customers and OEMs.

Industry: Developer Tools

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Cleveland, United States

Founded: 1923

Website LinkedIn

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Applied Industrial Technologies

5 months ago

Data & ML Pipeline Software Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 10 hours agoStatus: Live

Job Summary

Location: Sunnyvale

Workplace: Onsite

Employment Type: Full time

Job Function: Software Engineering

Key Responsibilities

•Build and maintain large-scale data processing pipelines (ETL) for ingesting and curating driving datasets
•Design and implement systems that automate data selection, labeling, training, and testing loops
•Collaborate with modeling teams to improve training efficiency and model performance across iterations
•Develop the core infrastructure that closes the loop between real-world test results and new model deployments
•Mentor junior engineers and contribute to defining best practices for data-centric development

Pay and Benefits

Salary: USD 125,000 - 222,000 annually

Equity and Bonus:Equity

Perks:Health InsuranceDentalVision401kLearning StipendPaid Leave

Key Requirements

•Bachelor's or higher degree in Engineering such as Computer Science, Electrical Engineering, Software Engineering
•3–5 years of experience in software or data infrastructure engineering
•Expertise in building and scaling data pipelines, distributed systems, or ML infrastructure
•Proficiency in Python and strong knowledge of data frameworks (Spark, Airflow, Kafka, etc.)
•Experience working with large-scale datasets and understanding data-driven development cycles

Experience:3-5 yearsAutonomous systemsData engineeringMachine learningData pipelines

Education:Bachelor's

Skills:CommunicationProblem-solvingMentorship

Tech Stack:PythonSparkAirflowKafkaETLData pipelines

Company Brief

Applied Industrial Technologies

Industry: Developer Tools

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Cleveland, United States

Founded: 1923

Website LinkedIn