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Mlops Data Engineer Jobs in Arizona (NOW HIRING)

Master Electronics

Data Scientist II

Phoenix, AZ · On-site

... engineering, model training, hyperparameter tuning, evaluation, and deployment * Develop scalable data pipelines on Databricks; integrate experimentation and ML systems with modern data and MLOps ...

Champions Funding LLC

Data Scientist

Gilbert, AZ · On-site

Partner with data engineering, IT, and business teams to develop scalable data pipelines and deploy ... AI, MLOps, or related machine learning frameworks. * Experience developing, deploying, and ...

Hospice of the Valley

Senior Data & AI Engineer

Phoenix, AZ · Remote

$100K - $136K/yr

Position Profile The Senior Data & AI Engineer will need to have deep handson experience in ... Operationalize models with MLOps (experiment tracking, reproducibility, CI/CD, monitoring, drift ...

Hospice of the Valley

Senior Data & AI Engineer

Phoenix, AZ · On-site

$100K - $136K/yr

Position Profile The Senior Data & AI Engineer will need to have deep hands‑on experience in ... Operationalize models with MLOps (experiment tracking, reproducibility, CI/CD, monitoring, drift ...

Master Electronics

Data Scientist II

Phoenix, AZ

... engineering, model training, hyperparameter tuning, evaluation, and deployment * Develop scalable data pipelines on Databricks; integrate experimentation and ML systems with modern data and MLOps ...

Master Electronics

Data Scientist II

Phoenix, AZ

... MLOps platforms (Databricks, MLflow); establish CI/CD pipelines, version control, testing, and monitoring to ensure model quality and reliability * Partner with software engineers, data engineers ...

Staffingine LLC

AIML Engineer

Scottsdale, AZ · On-site

AIML Engineer Job Location: Scottsdale - Arizona - USA Job Type: Contract to Hire ... Design and implement scalable MLOps supportive data pipelines for data ingestion processing and ...

Deloitte

Senior Forward Deployed Engineer- AWS

Tempe, AZ

$100K - $137K/yr

Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation * Experience with MLOps/LLMOps ...

Deloitte

Lead Forward Deployed Engineer - AWS

Tempe, AZ

$98K - $129K/yr

Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation * Experience with MLOps/LLMOps ...

Deloitte

Forward Deployed Engineer- AWS

Tempe, AZ

Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation * Experience with MLOps/LLMOps ...

Entertainment Partners

AI Engineer

Tempe, AZ

Contribute to EP's Enterprise Context Engine - the governed, zero-data-retention AI context layer exposed via MCP to Tabnine Agent and Claude Code. * MLOps & Production Engineering * Build and ...

Entertainment Partners

AI Engineer

Tempe, AZ · On-site

Contribute to EP's Enterprise Context Engine - the governed, zero-data-retention AI context layer exposed via MCP to Tabnine Agent and Claude Code. * MLOps & Production Engineering * Build and ...

Accenture

Senior Data Scientist

Scottsdale, AZ · On-site

Collaborate with data engineers, software engineers, machine learning engineers, architects, cybersecurity specialists, and platform teams to operationalize scalable AI solutions using MLOps ...

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Showing results 21-40

All JobsMlops Data Engineer JobsMlops Data Engineer Jobs in Arizona

Mlops Data Engineer information

What is the difference between Mlops Data Engineer vs Data Scientist?

AspectMlops Data EngineerData Scientist
Required SkillsMachine learning deployment, cloud platforms, scripting, data pipelinesStatistical analysis, programming, data visualization, machine learning modeling
CertificationsCloud certifications, ML engineering coursesData science certifications, statistical courses
Work EnvironmentData pipelines, cloud infrastructure, ML deployment systemsData analysis, modeling, research environments
Industry UsageTech companies, AI-focused firms, cloud service providersResearch institutions, analytics firms, tech companies

The main difference between an Mlops Data Engineer and a Data Scientist lies in their focus areas. Mlops Data Engineers specialize in deploying, maintaining, and scaling machine learning models within production environments, emphasizing infrastructure and automation. Data Scientists primarily focus on analyzing data, building models, and deriving insights. Both roles require strong technical skills, but their day-to-day tasks and career paths differ significantly.

Are MLOps Data Engineers in demand?

MLOps Data Engineers are in high demand due to the increasing adoption of machine learning and AI across industries. They are skilled in deploying, managing, and maintaining machine learning models using tools like Docker, Kubernetes, and cloud platforms, making their expertise highly sought after in data-driven organizations.

What are the key skills and qualifications needed to thrive as an MLOps data engineer?

To thrive as an MLOps Data Engineer, you need a strong background in data engineering, machine learning workflows, and software development, usually supported by a degree in computer science or a related field. Expertise with cloud platforms (such as AWS, GCP, or Azure), CI/CD pipelines, containerization tools (like Docker and Kubernetes), and familiarity with orchestration frameworks are typically required, along with certifications in cloud or data engineering. Strong problem-solving abilities, collaboration, and clear communication set professionals apart in this role. These skills and qualities are critical to efficiently deploying scalable machine learning solutions and ensuring smooth collaboration between data science and engineering teams.

What are some common challenges MLOps data engineers face when deploying machine learning models into production?

MLOps Data Engineers often encounter challenges such as ensuring seamless integration between data pipelines and model serving infrastructure, managing consistent data quality, and automating model retraining and monitoring. Another common hurdle is maintaining scalability and reliability as data volumes grow, and efficiently collaborating with data scientists, software engineers, and DevOps teams. Addressing these challenges requires strong communication skills, familiarity with cloud platforms, and a proactive approach to troubleshooting and automation.

What is an MLOps data engineer?

MLOps Data Engineers are professionals who blend expertise in machine learning (ML), operations (Ops), and data engineering to streamline the deployment and management of ML models in production environments. They design and maintain data pipelines, automate workflows, and ensure the scalability, reliability, and reproducibility of machine learning systems. Their role bridges the gap between data scientists and IT operations, enabling seamless integration of ML models into real-world applications.

What is the salary of MLOps Data Engineer?

The salary of an MLOps Data Engineer typically ranges from $90,000 to $150,000 annually, depending on experience, location, and company size. Professionals with advanced skills in cloud platforms, automation, and machine learning tools may earn higher compensation.

What are popular job titles related to Mlops Data Engineer jobs in Arizona?

For Mlops Data Engineer jobs in Arizona, the most frequently searched job titles are:

What job categories do people searching Mlops Data Engineer jobs in Arizona look for?

The top searched job categories for Mlops Data Engineer jobs in Arizona are:

What cities in Arizona are hiring for Mlops Data Engineer jobs?

Cities in Arizona with the most Mlops Data Engineer job openings:

Mlops Data Engineer jobs near you

Data Scientist II

Master Electronics

Phoenix, AZ • On-site

Full-time

Medical, Life, Retirement, PTO

Re-posted 8 days ago

Job description

To be a family that uses our collective superpowers to do significant good.
Master Electronics has an exciting career opportunity for a Data Scientist.
As a Data Scientist, you'll be a key contributor in designing, building, and evaluating data-driven decision systems, with a strong emphasis on pricing optimization, experimentation (A/B testing), and causal analysis that directly influence product and business outcomes.
What you will do?
  • Design, build, and refine pricing and optimization models, including dynamic pricing, price elasticity estimation, margin optimization, and demand forecasting, that directly drive revenue and profitability decisions
  • Own the experimentation lifecycle: design and run A/B and multivariate tests, define success metrics and guardrails, determine sample sizes and test duration, analyze results with statistical rigor, and communicate causal impact to stakeholders
  • Apply causal inference techniques (uplift modeling, difference-in-differences, synthetic controls, instrumental variables) where randomized experiments aren't feasible
  • Translate business problems into ML solutions; build models for prediction, classification, or recommendation; implement feature engineering, model training, hyperparameter tuning, evaluation, and deployment
  • Develop scalable data pipelines on Databricks; integrate experimentation and ML systems with modern data and MLOps platforms (Databricks, MLflow); establish CI/CD pipelines, version control, testing, and monitoring to ensure model quality and reliability
  • Partner with software engineers, data engineers, product managers, and subject-matter experts; present insights and recommendations to technical and non-technical stakeholders; translate complex analyses into clear narratives
  • Research and apply emerging ML techniques; contribute to improving team standards and mentoring junior team members

What you bring to the table!
  • 3-5 years of professional experience as a data scientist or ML engineer, with a proven record of building and deploying ML models in production
  • Hands-on experience with pricing, revenue, or marketing optimization, such as price elasticity modeling, dynamic pricing, promotion optimization, or mathematical optimization methods
  • Demonstrated expertise in A/B testing and experimentation: hypothesis design, power analysis, sequential testing, guardrail metrics, and interpreting results under real-world constraints (novelty effects, interference, heterogeneous treatment effects)
    Hands-on Databricks experience for building and deploying data science workloads at scale
  • Master's degree in Computer Science, Statistics, Mathematics, Engineering, Operations Research, or a related quantitative fi eld, or a Bachelor's degree with 5+ years of equivalent professional experience
  • Strong programming skills in Python (plus experience in JavaScript), with proficiency in ML libraries (scikit-learn, PyTorch), data manipulation (pandas, SQL), and statistical analysis
  • Solid grounding in statistics: hypothesis testing, confidence intervals, regression, and Bayesian methods
  • Knowledge of MLOps tools and cloud platforms, especially Databricks (Spark, MLfl ow), AWS (S3,Redshift, SageMaker), or similar services
  • Excellent communication skills; ability to explain complex technical concepts to both technical and business audiences and to collaborate effectively across teams
  • Demonstrated ability to work independently on complex problems, manage multiple projects simultaneously, and deliver results in a fast-paced environment
    Preferred Qualifications
  • Advanced degree (Master's or PhD) in a relevant field (Statistics, Machine Learning, AI, Operations Research, Economics/Econometrics, etc.)
  • Experience with B2B or ecommerce pricing, such as quote optimization, contract pricing, or price-list management in a distribution or catalog business
  • Familiarity with experimentation platforms (in-house or commercial, e.g., Optimizely, Statsig, GrowthBook)and metric frameworks
  • Exposure to industry-specific domains such as ecommerce, marketing analytics, risk/fraud, supply chain, or logistics
  • Fluency with big data frameworks (Spark, Hadoop), streaming systems, and container/orchestration tools(Docker, Kubernetes)
  • Databricks certifications (e.g., Machine Learning Associate/Professional)
  • Knowledge of model explainability, interpretability techniques, and responsible AI

Why do you want to work with us?
Stay Healthy: World-class and affordable insurance plans ensure you and your family stay healthy
Secure Your Future: 401(k) match programwhere you are vested from day-one
Invest in Your Education: Tuition assistanceempowers you to further your education and career
Employee Assistance Program (EAP) and other incentives: Access to Perspectives, Healthcare Advocate, Working Advantage Discount Program, and more
Enjoy Work-Life-Harmony: Paid holidays, PTO accrual, Floating Holiday, and supportive personal and parental leave policies
Do Significant Good: Company-sponsored donation match 3 for 1, Volunteer Time Off (VTO) to give back to the community, and Employee Resource Groups
Provide Additional Financial Security: Company-funded and voluntary AD&D Life Insurance for you and your loved ones
If you want to learn more about our comprehensive benefits, visit: https://careers.masterelectronics.com/benefits-wellness
Equal Opportunity Employer
At Master Electronics, we thrive in a fast-paced, entrepreneurial environment where flexibility, professionalism, and a self-starter mindset aren't just preferred-they're essential. Headquartered in sunny Phoenix, AZ, we're a leading global authorized distributor of electronic components, and have been proudly family-owned for over 50 years.
What's our secret? It's simple: strong relationships, responsive service, and genuine added value. These principles have fueled our growth, allowing us to serve hundreds of thousands of customers in close partnership with world-class suppliers across the globe.
We're also deeply committed to building a workplace where everyone feels respected, supported, and empowered to succeed. Master Electronics is committed to providing equal employment opportunities for all applicants and employees. We do not unlawfully discriminate based on race, color, religion, sex (including pregnancy, gender identity, and sexual orientation), national origin, age, disability, veteran status, marital status, creed, or any other protected characteristic.
We provide reasonable accommodations in compliance with the ADA and other applicable laws, and we strictly prohibit harassment of any kind.
This commitment applies to every part of our workplace-from recruitment and hiring to promotions, training, compensation, benefits, and even company events.

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