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Remote Embedded Machine Learning Jobs in Arizona

Senior DevOps Engineer (US REMOTE)

Phoenix, AZ ยท Remote

$140K - $170K/yr

Experience with AI/machine learning technologies is strongly preferred. * Familiarity with TCP/IP ... Candidate can live anywhere in the United States. #LI-MP2 #LI-REMOTE Basic Requirements * 8+ years ...

You will have the flexibility to work fully remote from anywhere across Arizona. Insight at a ... At least 5 years specifically focused on Data Engineering, Analytics, or Machine Learning. * Cloud ...

Experience deploying AI, machine learning, or LLM-based capabilities into enterprise workflows ... LI-Remote The Compensation range for this role is 230,000 to 270,000 USD annually and may be ...

Data Analyst (REMOTE)

Phoenix, AZ ยท Remote

$115K - $126K/yr

... machine learning or statistical analysis, data engineering and data visualization related work. Communication Skills Excellent written and verbal communication skills. Strong organizational and ...

... embedded/embedded-within-system trainers, courseware, instructor-led and distributed learning ... ranges, remote instruction, and logistics-enabled training) that meet rigorous government ...

... embedded/embedded-within-system trainers, courseware, instructor-led and distributed learning ... ranges, remote instruction, and logistics-enabled training) that meet rigorous government ...

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Remote Embedded Machine Learning information

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

To thrive as a Remote Embedded Machine Learning Engineer, you need a solid background in embedded systems, machine learning algorithms, and programming languages like C/C++ and Python, often supported by a degree in computer science, electrical engineering, or related fields. Familiarity with microcontrollers, edge AI frameworks (such as TensorFlow Lite or Edge Impulse), and version control systems is typically required. Strong problem-solving skills, effective communication, and self-motivation are essential soft skills for collaborating remotely and troubleshooting complex issues. These skills ensure successful deployment of intelligent solutions on resource-constrained devices and effective teamwork in distributed environments.

What is a Remote Embedded Machine Learning Engineer?

A Remote Embedded Machine Learning Engineer is a professional who develops and deploys machine learning models on embedded systems like microcontrollers, IoT devices, and edge hardware, all while working remotely. Their work involves optimizing algorithms to run efficiently on devices with limited computing power, memory, and battery life. These engineers typically use frameworks such as TensorFlow Lite or TinyML to design intelligent features that operate directly on hardware, enabling real-time decision-making without relying heavily on cloud connectivity. They collaborate with cross-functional teams and often troubleshoot both software and hardware issues from a remote location.

What is the difference between Remote Embedded Machine Learning vs Remote Data Scientist?

AspectRemote Embedded Machine LearningRemote Data Scientist
Required CredentialsBachelor's or Master's in Computer Science, Electrical Engineering, or related fields; experience with embedded systems and ML frameworksBachelor's or Master's in Data Science, Statistics, or related fields; proficiency in data analysis and ML algorithms
Work EnvironmentEmbedded hardware devices, IoT systems, real-time processing environmentsCloud platforms, data analysis labs, remote offices
Employer & Industry UsageTech companies, IoT device manufacturers, automotive, roboticsFinance, healthcare, marketing, tech firms

Remote Embedded Machine Learning specialists focus on integrating ML models into embedded hardware for real-time applications, often working with IoT and robotics. In contrast, Remote Data Scientists analyze large datasets to extract insights, primarily working in cloud or office environments. Both roles require strong analytical skills but differ in technical focus and work settings.

What are some common challenges faced by Remote Embedded Machine Learning Engineers, and how can they be addressed?

Remote Embedded Machine Learning Engineers often encounter challenges related to hardware access, debugging embedded devices remotely, and collaborating with cross-functional teams across time zones. To address these, it's important to set up robust remote development environments, use simulation tools when physical hardware isn't available, and establish clear communication channels for effective teamwork. Regular virtual meetings and detailed documentation also help ensure alignment and smooth progress, despite the remote nature of the work.
What are the most commonly searched types of Embedded Machine Learning jobs in Arizona? The most popular types of Embedded Machine Learning jobs in Arizona are:
What cities in Arizona are hiring for Remote Embedded Machine Learning jobs? Cities in Arizona with the most Remote Embedded Machine Learning job openings:

VP, Talent & Organizational Development

Cognite - AI for Industry

Phoenix, AZ โ€ข Remote

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 28 days ago


Job description

What Cognite is: Relentless to achieve

Cognite operates at the forefront of industrial digitalization, building AI, and data solutions that solve the world's hardest, highest-impact problems. With unmatched industrial heritage and a comprehensive suite of AI capabilities, including low-code AI agents, Cognite accelerates the digital transformation to drive operational improvements.

We thrive in challenges. We challenge assumptions. We execute with speed and ownership. If you view obstacles as signals to step forward - not backwards - you'll feel right at home here.

Our Moonshot is bold: Unlock $100B in customer value by 2035, and redefine how global industry works. Join us in this venture where AI and data meet ingenuity, and together, we will forge the path to a smarter, more connected industrial future.


How you'll demonstrate Ownership

The VP of Talent & Organizational Development is a transformative executive role for a leader who will architect how Cognite builds human capability at scale, in an era where the boundary between human expertise and AI augmentation is being redrawn in real time.

This role demands a rare profile: a strategic People leader with deep conviction about where AI is taking the workforce, the technical literacy to engage credibly, and the organizational design expertise to build structures that thrive. You will lead the functions of Talent, Leadership Development, Learning, Succession, and Organizational Effectiveness โ€” transforming each through AI-powered insight, tooling, and methodology.

Talent Strategy

  • Define Cognite's global talent strategy โ€” identifying where human capability must lead, where AI augments, and how the workforce of 2030 needs to be built today.
  • Deploy AI-driven talent intelligence to map external talent markets, predict attrition risk, and identify capability gaps before they become business constraints.

AI-Augmented Leadership & Organizational Development

  • Design leadership development programs explicitly built for an AI-augmented world โ€” developing leaders who can direct, collaborate with, and critically evaluate AI systems, not just manage people.
  • Introduce AI-powered coaching tools and continuous feedback platforms that give leaders real-time insight into their effectiveness and accelerate behavioral development at scale.
  • Build succession planning frameworks powered by predictive analytics โ€” moving from intuition-based talent reviews to data-driven readiness assessments with quantified risk and opportunity scoring.
  • Drive organizational design initiatives โ€” reimagining team structures, role definitions, and performance models for a world where AI agents are increasingly embedded in workflows.

AI-Enabled Learning & Capability Building

  • Architect a next-generation learning ecosystem powered by AI โ€” delivering personalized development paths that adapt to individual capability gaps, career goals, and real-time performance data.
  • Integrate AI tutors, simulation environments, and intelligent practice tools into Cognite's learning infrastructure, enabling employees to build skills faster and with greater retention.
  • Create structured reskilling and upskilling programs anticipating AI-driven role displacement and evolution โ€” transforming potential workforce disruption into a retention and development opportunity.

Culture, Engagement & Human-AI Inclusion

  • Champion a culture of human potential building psychological safety and growth mindsets that allow people to embrace AI as a collaborator.
  • Position Cognite as a model of responsible AI adoption in the workplace โ€” developing clear principles, communication strategies, and change programs that build trust in AI-powered people processes.

Talent Intelligence & Workforce Analytics

  • Build a world-class people analytics capability, transforming raw HR data into predictive workforce intelligence that drives strategic business decisions.
  • Develop dashboards and talent scorecards that give the executive team real-time visibility into leadership readiness, capability depth, engagement risk, and workforce trajectory.
  • Use machine learning models to forecast hiring needs, succession gaps, retention risks, and skill obsolescence โ€” enabling proactive rather than reactive talent decisions.
The Impact you bring to Cognite
  • A visionary People leader with genuine conviction about the transformative impact of AI on human capability, talent strategy, and organizational design.
  • Technical literacy that enables you to engage credibly with AI practitioners, evaluate tools critically, and distinguish genuine innovation from AI theater.
  • A proven systems architect โ€” able to connect talent strategy, AI tooling, organizational design, and culture into an integrated, self-reinforcing people architecture.
  • Exceptional executive presence, with the credibility to lead the workforce transformation conversation at the most senior levels of a global AI company.
  • A builder's mindset: as comfortable stress-testing a workforce planning model as you are presenting a board-level talent strategy.
  • Relentless curiosity โ€” someone who reads the research, experiments with new tools, and brings the outside in to keep Cognite's talent practices at the frontier.
Required Qualifications
  • 15+ years of progressive experience in talent management, organizational development, or related HR leadership roles, with significant exposure to technology-driven transformation.
  • At least 4โ€“5 years in a VP-level or equivalent senior leadership role in a high-growth global technology company.
  • Strong command of people analytics tools and platforms, with the ability to translate data into executive-level strategic recommendations.
  • Experience navigating rapid organizational scaling, including workforce redesign in the context of automation and AI-driven role evolution.
  • Location: Hybrid, based in Phoenix, Arizona

Preferred Experience

  • Experience in SaaS, AI, or industrial technology environments โ€” familiarity with engineering and technical talent markets is a strong plus.
  • Background in companies navigating high-growth transitions or pre-IPO organizational maturation.
  • Experience in industrial technology, SaaS, or AI-native companies โ€” with familiarity in attracting and retaining engineering and applied science talent.
  • Advanced degree (MBA, MS Organizational Psychology, MS Human-Computer Interaction, or similar) or relevant certification (SHRM-SCP, CIPD Level 7, ICF).
A snapshot of our many perks and benefits as a Cogniter
* Competitive compensation
* 401(k) with employer matching
* Competitive health, dental, vision & disability coverages for employees and all dependents
* Unlimited PTO
* Paid Parental Leave Program
* Employee Referral Program
Learn more about us
  • Impact 2025
  • Cognite's Industrial AI: Moonshot
  • We're globally recognized domain experts with an international presence that spans Phoenix, Houston, Oslo Tokyo, Bengaluru, and Abu Dhabi.
Equal Opportunity
Cognite is committed to creating a diverse and inclusive environment at work and is proud to be an equal opportunity employer. All qualified applicants will receive the same level of consideration for employment.