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Mosaic Ml Jobs (NOW HIRING)

subway

Sr Data Engineer

Shelton, CT

$106K - $144K/yr

Build GenAI and ML enablement patterns (RAG, feature stores, semantic layers) using Databricks Mosaic AI or Snowflake Cortex. * Partner with Data Science and Analytics teams to operationalize models ...

subway

Sr Data Engineer

Shelton, CT

$106K - $144K/yr

Build GenAI and ML enablement patterns (RAG, feature stores, semantic layers) using Databricks Mosaic AI or Snowflake Cortex. * Partner with Data Science and Analytics teams to operationalize models ...

subway

Sr Data Engineer

Shelton, CT

$106K - $144K/yr

Build GenAI and ML enablement patterns (RAG, feature stores, semantic layers) using Databricks Mosaic AI or Snowflake Cortex. * Partner with Data Science and Analytics teams to operationalize models ...

subway

Sr Data Engineer

Shelton, CT

$106K - $144K/yr

Build GenAI and ML enablement patterns (RAG, feature stores, semantic layers) using Databricks Mosaic AI or Snowflake Cortex. * Partner with Data Science and Analytics teams to operationalize models ...

subway

Sr Data Engineer

Shelton, CT · On-site

$106K - $144K/yr

Build GenAI and ML enablement patterns (RAG, feature stores, semantic layers) using Databricks Mosaic AI or Snowflake Cortex. * Partner with Data Science and Analytics teams to operationalize models ...

subway

Sr Data Engineer

Shelton, CT

$106K - $144K/yr

Build GenAI and ML enablement patterns (RAG, feature stores, semantic layers) using Databricks Mosaic AI or Snowflake Cortex. * Partner with Data Science and Analytics teams to operationalize models ...

subway

Sr Data Engineer

Shelton, CT

$106K - $144K/yr

Build GenAI and ML enablement patterns (RAG, feature stores, semantic layers) using Databricks Mosaic AI or Snowflake Cortex. * Partner with Data Science and Analytics teams to operationalize models ...

Databricks

Sr. Software Engineer- Backend

New York, NY · On-site +1

Databricks Mosaic AI is one of our fastest-growing businesses helping thousands of our customers ... Collaborate with platform, infra, and ML teams to deliver seamless end-to-end experiences * Shape ...

New

Databricks

Staff Backend Software Engineer

New York, NY · On-site +1

Databricks Mosaic AI is one of our fastest-growing businesses, helping thousands of our customers ... Collaborate with platform, infra, and ML teams to deliver seamless end-to-end experiences * Shape ...

SPECTRA TECH INC

Solutions Architect 4

Los Alamos, NM

$58.75 - $77.25/hr

Advise on the Databricks reference architecture covering Lakeflow, Delta Lake, Unity Catalog Mosaic ... and AI/ML teams participate in architecture reviews and contribute to standards Work with ...

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Mosaic Ml information

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$59.5K

$111.6K

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How much do mosaic ml jobs pay per year?

As of Aug 8, 2026, the average yearly pay for mosaic ml in the United States is $111,632.00, according to ZipRecruiter salary data. Most workers in this role earn between $80,500.00 and $132,500.00 per year, depending on experience, location, and employer.

What is the difference between Mosaic Ml vs Data Analyst?

AspectMosaic MlData Analyst
Required CredentialsTypically requires machine learning, data science, or related certificationsOften requires statistics, data analysis, or business intelligence certifications
Work EnvironmentFocuses on developing ML models, coding, and algorithm optimizationInvolves data interpretation, reporting, and business insights
Employer & Industry UsageUsed in tech, finance, and data-driven companies for predictive modelingCommon across various industries for data reporting and decision support

While both roles work with data, Mosaic Ml primarily focuses on building and deploying machine learning models, requiring coding and algorithm skills. Data Analysts interpret data and generate reports to support business decisions. Understanding these differences helps in choosing the right career path or job search focus.

What is Mosaic ML?

Mosaic ML is a company that specializes in developing tools and infrastructure to make training large-scale machine learning models more efficient, affordable, and accessible. They provide a platform and software suite that allows organizations to customize, train, and deploy state-of-the-art AI models, including large language models (LLMs), without the massive computational resources typically required. Mosaic ML focuses on optimization techniques that reduce training time and cost, making advanced AI more attainable for businesses and research teams. Their technology is used across industries for tasks like natural language processing, computer vision, and generative AI applications.

What does Mosaic ML do?

Mosaic ML is a company that provides tools and infrastructure to help organizations train large-scale machine learning models more efficiently and cost-effectively. They focus on optimizing distributed training processes, often utilizing cloud resources and advanced algorithms to improve performance. Job roles at Mosaic ML may require knowledge of machine learning frameworks, distributed systems, and programming skills in Python or similar languages.

How does a Mosaic ML engineer typically collaborate with data scientists and product teams during a project?

Mosaic ML engineers work closely with data scientists to design, scale, and optimize machine learning models, ensuring they meet both technical and business requirements. They frequently participate in cross-functional meetings to align model development with product objectives, while also translating complex technical concepts for non-technical stakeholders. Collaboration often involves iterative feedback, code reviews, and the joint troubleshooting of model deployment issues, fostering a dynamic and supportive team environment. This teamwork not only accelerates project delivery but also offers engineers valuable exposure to different perspectives and skill sets.

What are the key skills and qualifications needed to thrive as a machine learning engineer at Mosaic ML, and why are they important?

To thrive as a Machine Learning Engineer at MosaicML, you need a strong background in computer science, statistics, and deep learning, often supported by a relevant degree and experience with large-scale model training. Familiarity with ML frameworks such as PyTorch or TensorFlow, distributed computing systems, and version control tools like Git is typically required. Strong problem-solving skills, teamwork, and effective communication help you collaborate and adapt in a fast-evolving field. These skills are crucial for building efficient machine learning systems and contributing to innovative AI research and deployment.
More about Mosaic Ml jobs
What cities are hiring for Mosaic Ml jobs? Cities with the most Mosaic Ml job openings:
What states have the most Mosaic Ml jobs? States with the most job openings for Mosaic Ml jobs include:
What job categories do people searching Mosaic Ml jobs look for? The top searched job categories for Mosaic Ml jobs are:
Mosaic Ml jobs near you
Infographic showing various Mosaic Ml job openings in the United States as of August 2026, with employment types broken down into 94% Full Time, 2% Part Time, and 4% Contract. Highlights an 82% Physical, 4% Hybrid, and 14% Remote job distribution, with an average salary of $111,632 per year, or $53.7 per hour.

Sr Data Engineer

subway

Shelton, CT

$106K - $144K/yr

Full-time

Medical, Life, Retirement

Re-posted 10 days ago

Subway rating

4.4

Company rating: 4.4 out of 10

Based on 2,048 frontline employees who took The Breakroom Quiz

98th of 106 rated fast food restaurants

Job description

 

Sr Data Engineer - Shelton, CT

Ready to build what’s next with one of the world’s most iconic brands? 

Why Join Subway? 

At Subway, we are not standing still. We are building. 

This is a business focused on what matters most: growing franchisee profitability, strengthening our brand and creating long-term value. The people who thrive here are the ones who want to make a real impact. 

You will not just do the work. You will shape it. 

We move fast. We think like owners. We make decisions that matter. We hold ourselves to a high standard because what we do directly impacts thousands of franchisees around the world. 

If you bring energy, accountability and a bias for action, you will fit right in. 

We take the work seriously, but we also know the best results come from teams that support each other, celebrate wins and show up ready to build something better every day. 

This is your chance to be part of what’s next. 

About the Role: 

The Sr Data Engineer is a senior-level, hands-on technical leader responsible for designing, building, and evolving Subway’s enterprise data platform on Snowflake or Databricks. This role serves as a technical authority and builder, driving Lakehouse architecture, engineering frameworks, and best practices across multiple data domains. The Sr Data Engineer operates with a high degree of autonomy, leading through working code and influence — shipping reference implementations, POCs, and platform-level solutions that other teams build upon. 

Responsibilities include but not limited to: 

  • Personally design and build reference implementations and production-grade frameworks on Databricks or Snowflake.
  • Design lakehouse platforms using Delta Lake or Iceberg Tables with Medallion (Bronze/Silver/Gold) architecture.
  • Define and evolve enterprise data standards, patterns, and reusable accelerators.
  • Ensure solutions align with data governance, security, scalability, and cost-efficiency standards.
  • Evaluate technologies through hands-on benchmarking — not vendor decks.
  • Build the first working version of complex pipelines, frameworks, and POCs (ingestion, CDC, streaming, DQ, observability, CI/CD).
  • Drive emerging tech (Iceberg, Lakeflow, Openflow, Cortex, Mosaic AI) from POC to production rollout.
  • Solve high-complexity performance, cost, and governance challenges at petabyte scale.
  • Identify and address systemic technical debt and architectural risks.
  • Implement Lambda or Kappa architectures using Databricks Structured Streaming / DLT or Snowflake Dynamic Tables / Snowpipe Streaming.
  • Build GenAI and ML enablement patterns (RAG, feature stores, semantic layers) using Databricks Mosaic AI or Snowflake Cortex.
  • Partner with Data Science and Analytics teams to operationalize models and AI workflows.
  • Collaborate closely with Product, Architecture, Security, Infrastructure, and Analytics leaders.
  • Translate business needs into sound technical direction backed by working prototypes.
  • Communicate technical trade-offs, risks, and decisions clearly to technical and non-technical stakeholders.
  • Influence roadmaps and platform investments through technical insight and de-risking POCs.
  • Mentor Senior and Staff Data Engineers through pair-programming, PR reviews, and design coaching.
  • Raise engineering maturity by shipping working examples and codifying patterns.
  • Foster a culture of technical excellence, learning, and continuous improvement. 

Qualifications (some examples listed below): 

  • Exceptional hands-on expertise in Databricks or Snowflake lakehouse platforms.
  • Deep proficiency in PySpark or advanced SQL, plus Python for data engineering and automation.
  • Proven experience building Medallion architecture with Delta Lake or Iceberg Tables. 
  • Real-time and batch streaming experience (Lambda or Kappa) using Databricks DLT or Snowflake Dynamic Tables / Snowpipe Streaming. 
  • Hands-on with orchestration tools — Airflow, Databricks Lakeflow, or Snowflake Openflow; dbt experience a plus.
  • Strong data modeling skills (Dimensional, Data Vault, schema design).
  • Performance and cost tuning expertise (clustering, partitioning, Z-ordering, warehouse/cluster sizing, FinOps). 
  • Governance experience with Unity Catalog (Databricks) or Horizon Catalog (Snowflake) for lineage, access control, and data quality.
  • Semantic layer experience using Databricks AI/BI Genie / Unity Catalog Metrics or Snowflake Semantic Views / Cortex Analyst.
  • AI/ML enablement experience with Databricks Mosaic AI or Snowflake Cortex.
  • CI/CD and DevOps fluency — Git, Databricks Asset Bundles or Snowflake CLI / Schemachange, automated testing.
  • Cloud ecosystem expertise — AWS (S3, Glue, Kinesis), Azure, or GCP.
  • Excellent communication and technical storytelling ability.
  • Comfortable operating across ambiguity and complex stakeholder environments. 
  • Education: Bachelor’s degree required (Computer Science, Engineering, or related field); advanced degree preferred.
  • Experience: 3-5 years of professional data engineering experience, with proven track record leading architecture and hands-on build for enterprise-scale data platforms, operating in complex or mission-critical data environments, and influencing multiple teams and platforms without direct authority.
  • Travel Requirements: Minimal to moderate (up to 10%, as business needs require). 

What do we offer? 

  • Insurance Plans (Medical, Life)
  • Pension/401K/RSP (country specific)
  • Competitive Bonus
  • Mobility Allowance
  • Tuition Reimbursement
  • Company Holidays
  • Volunteering time
  • And More….. 

 

Compensation: The base pay range for this role is $102,700 - $128,400 annually

Pay within this range will be determined in good faith based on job-related factors, which may include skills, experience, education/training, location, and internal equity.

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