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Ai Ml Data Engineer Jobs (NOW HIRING)

AI/ML Data Engineer

Santa Clara, CA ยท On-site

$133.40K - $160.20K/yr

Embedded within the AI/ML team, this role owns the data engineering layer that powers both Gen AI applications and ML model development. Responsible for building production-grade pipelines, curating ...

AI/ML Data Engineer

Santa Clara, CA ยท On-site

$134.50K - $161.50K/yr

Your Team, Your Impact Embedded within the AI/ML team, this role owns the data engineering layer that powers both Gen AI applications and ML model development. Responsible for building production ...

AI/ML Data Engineer

Santa Clara, CA ยท On-site

$134.50K - $161.50K/yr

Your Team, Your Impact Embedded within the AI/ML team, this role owns the data engineering layer that powers both Gen AI applications and ML model development. Responsible for building production ...

AI Data Engineer

Spring, TX ยท On-site

$96.90K - $116.40K/yr

Design and implement data pipelines that support AI/ML workflows, including feature engineering and model monitoring. Integrate AI-powered analytics and predictive models into business intelligence ...

$65.75 - $84.75/hr

Senior AI/ML Data Architect We are seeking a Senior AI/ML Data Architect with strong expertise in ... Data Pipelines & Engineering Design and oversee end-to-end data pipelines covering ingestion ...

AI/ML Data Architect

Basking Ridge, NJ ยท On-site

$65.75 - $84.50/hr

, We are seeking a Senior AI/ML Data Architect with strong expertise in Large Language Models (LLMs ... Data Pipelines & Engineering Design and oversee end'to?end data pipelines covering ingestion ...

AI Data Engineer

Fort Belvoir, VA ยท On-site +1

$129.50K - $155.50K/yr

The AI Data Engineer will design, develop, and maintain data pipelines and architectures to support AI/ML workloads for the Army Intelligence & Security Enterprise (AISE). This role ensures data ...

AI Data Engineer

Fort Belvoir, VA ยท On-site

$129.50K - $155.50K/yr

The AI Data Engineer will design, develop, and maintain data pipelines and architectures to support AI/ML workloads for the Army Intelligence & Security Enterprise (AISE). This role ensures data ...

AI Data Engineer

Fort Belvoir, VA ยท Remote

$129.50K - $155.50K/yr

The AI Data Engineer will design, develop, and maintain data pipelines and architectures to support AI/ML workloads for the Army Intelligence & Security Enterprise (AISE). This role ensures data ...

Data Engineer

San Jose, CA ยท On-site

$134.20K - $161.10K/yr

AI/ML Data Preparation: Collaborate closely with Data Scientists and Machine Learning Engineers to understand data requirements for model training, evaluation, and serving. Prepare, transform, and ...

AI Data Engineer

Fort Belvoir, VA ยท On-site

$129.50K - $155.50K/yr

The AI Data Engineer will design, develop, and maintain data pipelines and architectures to support AI/ML workloads for the Army Intelligence & Security Enterprise (AISE). This role ensures data ...

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Ai Ml Data Engineer information

See salary details

$44.5K

$129.7K

$177.5K

How much do ai ml data engineer jobs pay per year?

As of May 28, 2026, the average yearly pay for ai ml data engineer in the United States is $129,716.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,500.00 and $137,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an AI/ML Data Engineer, and why are they important?

To thrive as an AI/ML Data Engineer, you need a strong background in computer science, proficiency in programming languages like Python or Scala, and experience with data modeling, ETL pipelines, and machine learning concepts. Familiarity with big data tools (such as Hadoop, Spark), cloud platforms (AWS, GCP, Azure), and relevant certifications like Google Professional Data Engineer or AWS Certified Machine Learning are highly valuable. Strong problem-solving, collaboration, and communication skills help you work effectively within cross-functional teams and translate business needs into technical solutions. These skills ensure you can efficiently build scalable data architectures and support robust AI/ML solutions that drive business innovation.

What are some common challenges faced by AI/ML Data Engineers when working on large-scale machine learning projects?

AI/ML Data Engineers often encounter challenges such as managing and optimizing massive datasets, ensuring data quality and consistency, and maintaining efficient data pipelines. They must also handle the integration of diverse data sources and collaborate closely with data scientists and software engineers to deploy machine learning models into production. Addressing scalability and performance bottlenecks is a frequent part of the role, requiring strong problem-solving skills and familiarity with distributed computing frameworks.

What are AI/ML Data Engineers?

AI/ML Data Engineers are professionals who design, build, and maintain data pipelines and infrastructure to support artificial intelligence (AI) and machine learning (ML) applications. They are responsible for collecting, cleaning, and organizing large datasets, ensuring data quality, and enabling data scientists and ML engineers to develop and deploy models efficiently. Their work often involves using programming languages like Python or Scala, big data technologies, and cloud platforms. In essence, AI/ML Data Engineers bridge the gap between raw data and actionable insights in AI and ML projects.

What is the difference between Ai Ml Data Engineer vs Data Scientist?

AspectAi Ml Data EngineerData Scientist
Primary FocusBuilding data pipelines, deploying ML models, managing data infrastructureAnalyzing data, developing models, deriving insights
Skills & CertificationsProgramming (Python, SQL), cloud platforms, data engineering toolsStatistics, machine learning, data analysis, Python/R
Work EnvironmentData engineering teams, cloud environments, big data platformsResearch teams, analytics departments, business units

While both roles involve working with data and machine learning, Ai Ml Data Engineers focus on building and maintaining data pipelines and deploying models, whereas Data Scientists primarily analyze data and develop predictive models. The roles often collaborate but serve different functions within data projects.

More about Ai Ml Data Engineer jobs
What cities are hiring for Ai Ml Data Engineer jobs? Cities with the most Ai Ml Data Engineer job openings:
What states have the most Ai Ml Data Engineer jobs? States with the most job openings for Ai Ml Data Engineer jobs include:
What job categories do people searching Ai Ml Data Engineer jobs look for? The top searched job categories for Ai Ml Data Engineer jobs are:
Infographic showing various Ai Ml Data Engineer job openings in the United States as of May 2026, with employment types broken down into 72% Full Time, 24% Part Time, and 4% Contract. Highlights an 17% Physical, 7% Hybrid, and 76% Remote job distribution, with an average salary of $129,716 per year, or $62.4 per hour.
AI/ML Data Engineer

AI/ML Data Engineer

Marvell

Santa Clara, CA โ€ข On-site

$133.40K - $160.20K/yr

Other

Life, Retirement

This job post hasย expired today.ย Applications are no longer accepted.


Job description

Data Engineer

Marvell's semiconductor solutions are the essential building blocks of the data infrastructure that connects our world. Across enterprise, cloud and AI, and carrier architectures, our innovative technology is enabling new possibilities.

At Marvell, you can affect the arc of individual lives, lift the trajectory of entire industries, and fuel the transformative potential of tomorrow. For those looking to make their mark on purposeful and enduring innovation, above and beyond fleeting trends, Marvell is a place to thrive, learn, and lead.

Embedded within the AI/ML team, this role owns the data engineering layer that powers both Gen AI applications and ML model development. Responsible for building production-grade pipelines, curating AI-ready datasets for LLMs and ML models, and contributing to front-end interfaces when required โ€” ensuring the team can deliver complete, data-driven AI products without external dependency.

What You Can Expect

Key Responsibilities
  • Architect and deliver production-grade ELT/ETL pipelines across Databricks and Snowflake for ML training, validation, and inference workflows
  • Build and maintain AI-ready datasets optimized for both ML model consumption and Gen AI use cases โ€” clean, versioned, and reproducible
  • Curate and structure high-quality datasets for RAG pipelines and embedding generation; design document chunking strategies, metadata schemas, and grounding data layers that directly improve retrieval accuracy and Gen AI application performance
  • Implement data quality frameworks and data contracts at pipeline boundaries to protect model and application integrity
  • Build and manage vector-ready data assets, integrating with vector stores and embedding infrastructure for Gen AI applications
  • Establish DataOps best practices โ€” CI/CD for pipelines, data lineage, versioning, and cost observability across platforms
  • Develop Streamlit applications and React-based UIs to surface model outputs, data products, and internal AI tooling
  • Partner with ML Engineers, Data Scientists, and AI Engineers to translate modeling and application requirements into reliable data products
  • Contribute to lakehouse architecture decisions, storage optimization, and compute efficiency across the AI/ML data platform

What We're Looking For

Required Skills
  • Databricks โ€” Spark, Delta Lake, Databricks Workflows, Unity Catalog; production-grade experience required
  • Snowflake โ€” advanced SQL, data modeling, performance tuning, cost management
  • Python โ€” strong engineering fundamentals; PySpark, pandas, pipeline frameworks (dbt, Airflow, or equivalent)
  • SQL โ€” expert level; complex transformations, query optimization, schema design
  • Front-End Development โ€” React, JavaScript/TypeScript, REST API integration, and Streamlit for rapid AI/ML application prototyping and internal tooling
  • Solid understanding of ML lifecycle โ€” feature stores, training pipelines, inference data patterns
  • Cloud-native experience on AWS, Azure, or GCP
  • Data quality and observability tooling
Nice to Have
  • Hands-on experience with MLflow, Feast, LangChain, or LlamaIndex
  • Exposure to graph databases (Neo4j, Neptune, or equivalent)
  • Exposure to vector databases (Pinecone, Weaviate, pgvector, or equivalent)
  • Experience with streaming pipelines (Kafka, Kinesis, Spark Structured Streaming)
  • Familiarity with LLM evaluation frameworks and dataset benchmarking

Expected Base Pay Range (USD)

105,200 - 157,600, $ per annum

The successful candidate's starting base pay will be determined based on job-related skills, experience, qualifications, work location and market conditions. The expected base pay range for this role may be modified based on market conditions.

Additional Compensation and Benefit Elements

Marvell is committed to providing exceptional, comprehensive benefits that support our employees at every stage - from internship to retirement and through life's most important moments. Our offerings are built around four key pillars: financial well-being, family support, mental and physical health, and recognition. Highlights include an employee stock purchase plan with a 2-year look back, family support programs to help balance work and home life, robust mental health resources to prioritize emotional well-being, and a recognition and service awards to celebrate contributions and milestones. We look forward to sharing more with you during the interview process.

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status.

Any applicant who requires a reasonable accommodation during the selection process should contact Marvell HR Helpdesk at TAOps@marvell.com.

Interview Integrity

To support fair and authentic hiring practices, candidates are not permitted to use AI tools (such as transcription apps, real-time answer generators like ChatGPT or Copilot, or automated note-taking bots) during interviews.

These tools must not be used to record, assist with, or enhance responses in any way. Our interviews are designed to evaluate your individual experience, thought process, and communication skills in real time. Use of AI tools without prior instruction from the interviewer will result in disqualification from the hiring process.

This position may require access to technology and/or software subject to U.S. export control laws and regulations, including the Export Administration Regulations (EAR). As such, applicants must be eligible to access export-controlled information as defined under applicable law. Marvell may be required to obtain export licensing approval from the U.S. Department of Commerce and/or the U.S. Department of State. Except for U.S. citizens, lawful permanent residents, or protected individuals as defined by 8 U.S.C. 1324b(a)(3), all applicants may be subject to an export license review process prior to employment.