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Senior Embedded Machine Learning Jobs in Illinois

Autodesk

Senior Machine Learning Test Engineer

Ohio, IL · On-site +1

$104K - $135K/yr

Job Requisition ID # 26WD98377 Senior Machine Learning Test Engineer Location: United States East Coast Position Overview As a Senior Machine Learning Test Engineer in the Research Enablement team ...

Cccis

Senior Manager - Machine Learning

Chicago, IL · On-site

The Role We are seeking a Senior Manager to lead our Machine Learning (ML) team in the subrogation business. This role is critical to expanding the emerging subrogation market for CCC and as such is ...

Aquabyte

Embedded Software Engineer

Mundelein, IL

$130K - $190K/yr

Through custom underwater cameras, computer vision, and machine learning we are able to quantify ... Improve our embedded Linux build and deployment process * Develop software to automate hardware ...

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Senior Embedded Machine Learning information

What is the difference between Senior Embedded Machine Learning vs Embedded Software Engineer?

AspectSenior Embedded Machine LearningEmbedded Software Engineer
Required CredentialsBachelor's/Master's in CS, EE, or related; experience in ML and embedded systemsBachelor's in CS, EE, or related; strong programming skills in C/C++
Work EnvironmentDeveloping ML models for embedded devices, hardware integrationDesigning and implementing embedded software for devices
Industry UsageAI/ML-focused companies, IoT, consumer electronicsAutomotive, industrial, consumer electronics

While both roles involve embedded systems, Senior Embedded Machine Learning focuses on integrating ML models into hardware, requiring knowledge of AI and data science. Embedded Software Engineers primarily develop software for embedded devices, emphasizing firmware and system-level programming. The roles overlap in embedded environment skills but differ in their core focus on AI versus traditional software development.

What are some common challenges faced by Senior Embedded Machine Learning Engineers when deploying models on edge devices?

Senior Embedded Machine Learning Engineers often encounter challenges such as optimizing model size and inference speed to fit within the limited computational resources and memory of edge devices. Balancing accuracy and performance while minimizing power consumption is critical, especially for battery-operated products. Additionally, integrating models with existing embedded software and ensuring reliable, real-time operation can require close collaboration with hardware and firmware teams. Staying current with advancements in model compression and hardware acceleration is also essential for success in this role.

What are the key skills and qualifications needed to thrive as a Senior Embedded Machine Learning Engineer, and why are they important?

To thrive as a Senior Embedded Machine Learning Engineer, you need expertise in embedded systems, machine learning algorithms, and programming languages like C/C++ and Python, often backed by an advanced degree in computer science or electrical engineering. Familiarity with tools such as TensorFlow Lite, ONNX, and embedded hardware platforms (e.g., ARM Cortex-M, NVIDIA Jetson) is typically required. Strong problem-solving, project management, and communication skills distinguish top performers in this role. These capabilities are crucial for efficiently deploying optimized machine learning models on resource-constrained devices and effectively collaborating across multidisciplinary teams.

What does a Senior Embedded Machine Learning engineer do?

A Senior Embedded Machine Learning engineer designs, develops, and optimizes machine learning models to run efficiently on resource-constrained embedded devices such as microcontrollers, IoT devices, and edge hardware. They are responsible for integrating ML algorithms with embedded systems, ensuring low latency and minimal power consumption. Their work often involves collaborating with hardware engineers and software developers to deploy intelligent features in products like smart sensors, wearables, and autonomous systems.
What are the most commonly searched types of Embedded Machine Learning jobs in Illinois? The most popular types of Embedded Machine Learning jobs in Illinois are:
Senior Embedded Machine Learning jobs near you

Senior Director, Data Science & Gen AI

Bcbsa

Chicago, IL • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 4 days ago

Job description

Job Description Summary
The Senior Director, Data Science and GenAI is a senior leadership role focused on leading the development and application of Generative AI and advanced machine learning capabilities embedded across BCBSA's data and analytic assets. This role strategically sets the direction and portfolio of activities to embed AI into BCBSA's Blue System of intelligence data assets, and work across the BCBS System to make those capabilities available to BCBS Plans.
This role sets the technical and analytic direction for Generative AI and Machine Learning capabilities embedded across BCBS System data assets and BHI's Plan-level product offerings, operating in environments characterized by high ambiguity, rapid technological evolution, and complex data ecosystems. The Senior Director applies deep expertise in advanced analytics, machine learning, and GenAI to evaluate tradeoffs, establish standards, and guide critical decisions related to model selection, architecture, performance, scalability, and responsible AI practices. The role is accountable for navigating complex, non-routine problem spaces and translating emerging technologies into sustainable, enterprise-grade product capabilities with measurable business impact on cost of care, quality improvement, product differentiation, and revenue growth.
This role serves as a subject matter expert across the BCBS System and the broader healthcare industry in advanced data science, applying machine learning, statistical, and mathematical techniques across heterogeneous and complex healthcare data. This role leads BCBSAs efforts to innovate and implement emerging AI technologies in its enterprise data and analytics assets, and acts as a executive thought leader to BCBSA technology and analytics committees . This leader works within BCBSA and BCBS Plans to set standards and best practices for computational, algorithmic, and predictive analytics to ensure solutions are scalable, responsible, and enterprise-ready.
Working closely with Product, Engineering, and other BHI data science teams, the Senior Director leads end-to-end GenAI initiatives-from opportunity identification and proof-of-concept development through validation and production deployment-while maintaining a hands-on role in the most complex, high-risk, or novel analytic and GenAI designs. The role also mentors a high-performing data science team and advises leadership on the effective use of Generative AI to drive product differentiation and measurable business impact.

Job Description

Responsible for settingthe enterprise technical and analytic strategy for Generative AIfor BCBSA's BSI and national data assets, including long-term vision, architectural direction,capability roadmap, and standards for scalable, responsible AI embedded across all products.

Serve as a trusted advisor to executive leadership, with accountability for key technical and analytic decisions, translating complex models and analytic findings into actionable insights that inform and activate business strategies.

Lead and individually contribute to large-scale data science initiatives, including end-to-end machine learning and GenAI model development, experimentation, and implementation.

Act as the subject matter expert in computational algorithms, model evaluation, and advanced data interpretation to assess performance, tradeoffs, and impact.

Lead and manage data science and machine learning R&D efforts acrossmultiple product lines, data domains (medical, pharmacy, emerging clinical data), and customer-facing platforms.

Partner with ProductStrategytoidentifyand apply Generative AI and advanced analytics within the product development process, with a focus on emerging healthcare trends and priorities.

Collaborate closely with Data Engineering to design scalable applications andoptimaldataarchitectureleveragingstructured and unstructured data.

Establish and govern enterprise standardsand best practices for analysis plans, ensuring rigor, reproducibility, ethical AI use, and compliance with regulatory and security requirements.

Drive education and adoption of data science and Generative AI across the organization by communicating vision, use cases, and value.

Manage and develop senior data science talent, supporting professional growth andsuccessionreadiness.

Manage external analytics vendors and partnerships, including relationships with AI vendors and academic experts in LLMs and NLP.

Work with executive leadership and cross-functional stakeholders to define requirements and develop AI and analytics R&D and strategic roadmaps.

Evaluate and implement new AI, ML, and Generative AI tools and technologies to enhance organizational capability and competitiveness.

Oversee the development of training datasets, data preprocessing pipelines, and testing frameworks to support advanced analytics and AI solutions.

The posting range for this position is:
$215,000.00-$295,000.00

Qualifications:

Education

  • Master's Degree Focused on machine learning (ML) or adjacent fields, including Analytics, Data Science, Statistics, Mathematics, Computer Science, or a related field

Experience

  • At least 15 years experience with progressively more complex data science, applied statistics, machine learning, or mathematical modeling projects.

  • Experience withstreaming and near-real-time data in healthcare (such as HL7 streams or FHIR applications) industry.

  • Experience withestablishingand governing a Machine Learning Operationalization (MLOps) program, including the use ofMLOpstools (e.g.,MLFlow, Kubeflow).

  • Experience with major cloud computing platforms, AWS experience is highly preferred.

  • Experience with cloud-based data-as-a-service platforms (e.g., Snowflake, Synapse, Databricks).

  • Experience with Agile development practices, including development frameworks (e.g., Scrum or Kanban) and tools for continuous integration and deployment (CI/CD).

  • Experience working with Generative AI (GenAI), Large Language Models (LLM), Natural Language Processing (NLP), and other advanced analytics.

Knowledge Skills and Abilities

  • Strong fundamental knowledge of probability theory, stochastic systems, Bayesian inference, predictive modeling, supervised/unsupervised/deep learning Natural language processing experience, particularly in the biological and medical domains.

  • A record of successful formulation, approval, and implementation of organizational strategies around advanced analytics in AI/ML.

  • Expertisein using machine learning and analytic tools such as SQL, R, and/or Python to analyze data in applied professional projects.

  • Familiarity with relational databases (e.g., MS SQL, Oracle, Postgres, MySQL).

  • Expertise in visualizing and manipulating big data sets.

  • Strong verbal and written communications skills with the demonstrated ability to explain complex technical concepts to a lay audience.

  • Demonstrated ability to deliver successful, profitable, repeatable, referenced analytic solutions.

  • Proven ability to develop staff to deliver world-class analytic solutions.

  • Knowledgeable in complex modeling topics, advanced statistics/biostatistics, algorithm design, and ML software packages.

    #LI_HYBRID

    The posted salary range is the lowest to highest salary we, in good faith, believe we would pay for this role at the time of this posting. We may ultimately pay more or less than the hiring range and this hiring range may also be modified in the future. A candidate's position within the hiring range may be based on several factors including, but not limited to, specific competencies, relevant education, qualifications, certifications, relevant experience, skills, seniority, performance, shift, travel requirements, and business or organizational needs.This job is also eligible for annual bonus incentive pay.

    We offer a comprehensive package of benefits including paid time off, 11 holidays, medical/dental/vision insurance, generous 401(k) matching, lifestyle spending account and many other benefits to eligible employees.

    Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, commission, or any other form of compensation that are allocable to a particular employee remains in the Company's sole discretion unless and until paid and may be modified at the Company's sole discretion, consistent with the law.

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