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Mosaic Ml Jobs (NOW HIRING)

AI/ML Data Engineer

$117K - $140K/yr

The AI/ML Engineer builds, deploys, and supports production forecasting and AI capabilities on top ... Preferred Qualifications Experience with MLflow, Mosaic AI Model Serving, Unity Catalog-governed AI ...

AI/ML Data Engineer

$117K - $140K/yr

The AI/ML Engineer builds, deploys, and supports production forecasting and AI capabilities on top ... Preferred Qualifications • Experience with MLflow, Mosaic AI Model Serving, Unity Catalog ...

Mosaic, our in‑house toolkit for rapidly deploying agentic workflows * Strategic partnerships ... Have depth in LLM and ML fundamentals. * Are comfortable implementing and debugging large‑scale ...

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Mosaic Ml information

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$59.5K

$111.6K

$203K

How much do mosaic ml jobs pay per year?

As of Aug 23, 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 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.

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.

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.

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:

Infographic showing various Mosaic Ml job openings in the United States as of August 2026, with employment types broken down into 1% Internship, 95% Full Time, 1% Part Time, and 3% Contract. Highlights an 78% Physical, 6% Hybrid, and 16% Remote job distribution, with an average salary of $111,632 per year, or $53.7 per hour.

Member of Technical Staff, Software Engineering, Mosaic Reporting

Cognita Imaging Inc.

Palo Alto, CA • On-site

$190 - $210/hr

Other

Posted 5 days ago


Job description

Member of Technical Staff, Software Engineering, Mosaic Reporting

Cognita Imaging

Level: Senior / Staff

Type: Full-time

Location: San Francisco Bay Area (in-person), Remote or Hybrid

Cognita's mission is to increase the world's access to healthcare. Radiology is (1) the first-line diagnostic specialty, (2) facing a worsening global workforce shortage, and (3) highly digitized, making it uniquely positioned for AI to have an enormous impact. Stage one of Cognita is focused on expanding access to radiology at scale.

Our founding team met at Stanford, where they laid the groundwork for applying comprehensive AI to radiology. Building on that foundation, Cognita develops vision-language models that read radiology studies the way radiologists do, interpreting the full study in clinical context, and generating draft results that make radiologists more efficient and accurate. In partnership with Radiology Partners, the largest radiology practice in the world, Cognita's models are trained and validated on one of the world's largest real-world radiology datasets.

About the Role

As a Member of Technical Staff in Software Engineering, you will build the full-stack systems behind Mosaic Reporting, Cognita's AI-native, real-time radiology reporting product, part of MosaicOS. As a radiologist dictates, the system extracts statements from natural speech and places them into the correct section of the report in real time. Findings, impressions, macros, and edits are all driven by natural dictation rather than templated clicking, so the report comes together as the radiologist reads, with their eyes never leaving the image. This experience is powered by Cognita's proprietary real-time reporting technology.

Mosaic Reporting is already deployed across thousands of radiologists at Radiology Partners and is proven in production. Your work focuses on the next chapter: scaling and improving the system as it rolls out more broadly across Radiology Partners and to external customers, work that sits directly in the critical path of patient care. You’ll be one of the first hires dedicated to transforming reporting into a revolutionary product, and you’ll work closely with our clinical AI teams to continuously improve the product experience for the radiologists who use it on every study. You’ll report to the Reporting product lead and partner across engineering, ML, and clinical teams to take the product from "works at scale" to "built to scale."

Your Impact
  • Iterate on the frontend and backend services that power Mosaic Reporting.
  • Improve our reporting system that transforms model outputs and radiologist voice dictation into accurate, structured radiology reports in real time.
  • Develop workflows for VLM-based pixel-to-text report drafting, editing, resident workflows and clinician sign-off.
  • Help scale and harden the real-time streaming dictation pipeline so the system stays efficient and reliable as the load and the team grow.
  • Work with large volumes of structured and unstructured data, including imaging metadata and model outputs.
  • Ensure platform services are reliable, secure, low-latency, and scalable as the product expands across Radiology Partners and to external customers.
  • Collaborate closely with clinical AI, ML training, evaluation, and infrastructure teams to integrate inference into production reporting workflows and improve product quality.
  • Own services end-to-end, from design and implementation through deployment and operation.
What You Bring
  • We are not credential-driven. We only look for evidence of exceptional ability.
  • Strong experience building full-stack systems in production.
  • Attention to detail and an eye for product design
  • Experience designing and operating cloud-based services, ideally on AWS.
  • Comfort building and owning API-driven, data-intensive systems.
  • Experience working with distributed systems and production reliability concerns.
  • Experience with real-time and/or low-latency systems (streaming, WebSocket/WebRTC, SSE, or similar) is a strong plus.
  • Familiarity with a modern backend stack such as:
    • AWS (e.g., EC2, S3, ECS/EKS, IAM, CloudWatch)
    • Python backend services (e.g. FastAPI, Flask, or similar)
    • PostgreSQL or similar relational databases
  • Strong ownership mindset and good systems judgment.
What Sets You Apart
  • Experience with report generation, structured text pipelines, or document workflows.
  • Familiarity with LLM inference pipelines or AI-powered products
  • Experience working in healthcare or other regulated environments, and handling PHI / building to HIPAA requirements
  • Radiology or medical imaging domain knowledge (modalities, reporting workflows, structured reporting).
  • Hands‑on with speech-to-text or low-latency audio streaming pipelines
  • React / Next.js performance and state architecture
Our Culture
  • We build from first principles. We question assumptions, reason from fundamentals, and execute with speed and clarity, without sacrificing quality.
  • We operate as a true meritocracy. Impact matters, rather than optics. Feedback is direct, respect is non-negotiable, and we support each other with the ownership, trust, and resources needed to do the best work of our careers.
  • Every decision we make is grounded in supporting clinicians to improve patient outcomes.

The salary range for this full-time position is: $190,000–$210,000 base, plus competitive equity

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