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Remote Machine Learning Robotics Jobs in North Carolina

... remote locations. ** About our Team : LexisNexis Legal & Professional, serving customers in over ... Machine Learning and AI Solutions : Lead the development and implementation of machine learning ...

... remote locations. ** About our Team : LexisNexis Legal & Professional, serving customers in over ... Machine Learning and AI Solutions : Lead the development and implementation of machine learning ...

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Remote Machine Learning Robotics information

What is a remote machine learning robotics job?

A Remote Machine Learning Robotics job involves developing and implementing machine learning algorithms to control and improve robotic systems, all while working from a remote location. Professionals in this field use artificial intelligence techniques to enable robots to learn from data and adapt to new tasks. They collaborate with teams virtually, leveraging cloud-based tools and simulation environments to design, test, and deploy robotic solutions. This role typically requires strong programming skills, knowledge of robotics frameworks, and experience with machine learning models.

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

AspectRemote Machine Learning RoboticsRemote Data Scientist
Required CredentialsDegree in Robotics, Computer Science, or related fields; experience with ML algorithms and robotics platformsDegree in Data Science, Statistics, or related fields; proficiency in ML, statistics, and programming
Work EnvironmentHands-on with robotics hardware, simulation environments, and software developmentData analysis, modeling, and visualization primarily on software platforms
Employer & Industry UsageRobotics companies, manufacturing, autonomous vehicles, research labsTech firms, finance, healthcare, research institutions

Remote Machine Learning Robotics focuses on developing intelligent systems that integrate robotics hardware with machine learning algorithms, often requiring hands-on hardware work. In contrast, Remote Data Scientists primarily analyze data and build models using software tools. Both roles involve ML expertise but differ in work environment and industry applications.

How do remote machine learning robotics professionals typically collaborate with hardware teams when working off-site?

Remote machine learning robotics professionals often collaborate closely with hardware teams through regular virtual meetings, shared documentation, and cloud-based development environments. They use simulation tools to test algorithms before deployment and rely on video calls or live streams to observe hardware tests in real time. Effective communication and detailed feedback are essential to ensure that software and hardware integration runs smoothly, despite working from different locations. This collaborative approach helps address issues quickly and keeps projects on track.

Can a remote machine learning robotics engineer work remotely?

Yes, remote machine learning robotics engineers can work remotely, especially if their role involves software development, data analysis, and algorithm design. Many companies support remote work for these positions, often requiring proficiency with collaboration tools and cloud-based platforms. However, some tasks involving hardware or on-site testing may require physical presence.

What are the key skills and qualifications needed to thrive as a remote machine learning robotics engineer?

To thrive as a Remote Machine Learning Robotics Engineer, you need a solid background in robotics, machine learning algorithms, programming (Python, C++), and typically a degree in computer science, robotics, or a related field. Familiarity with robotics frameworks (like ROS), machine learning libraries (such as TensorFlow or PyTorch), and experience with cloud platforms or remote collaboration tools are highly valued. Strong problem-solving abilities, initiative, and effective remote communication skills help you excel in distributed teams. These competencies enable you to develop intelligent robotic systems efficiently, collaborate across locations, and drive innovation in a rapidly evolving field.
What are popular job titles related to Remote Machine Learning Robotics jobs in North Carolina? For Remote Machine Learning Robotics jobs in North Carolina, the most frequently searched job titles are:
What job categories do people searching Remote Machine Learning Robotics jobs in North Carolina look for? The top searched job categories for Remote Machine Learning Robotics jobs in North Carolina are:
What cities in North Carolina are hiring for Remote Machine Learning Robotics jobs? Cities in North Carolina with the most Remote Machine Learning Robotics job openings:

Data Scientist / Machine Learning Engineer (Generative AI Focus)

Strategic Staffing Solutions

Charlotte, NC โ€ข On-site, Remote

Full-time

Re-posted 28 days ago


Job description

Job Description STRATEGIC STAFFING SOLUTIONS HAS AN OPENING. This is a Contract Opportunity with our company that MUST be worked on a W2 Only. No C2C eligibility for this position.

Visa Sponsorship is Available. The details are below. "Beware of scams.

S3 never asks for money during its onboarding process." Job Title: Data Scientist / Machine Learning Engineer (Generative AI Focus) Contract Length: 12+ Months Hybrid schedule 3 days per week onsite/ 2 remote Location: Charlotte, NC/ Irving, TX/ Boston, MA Ref# 246769 We are seeking a highly motivated Data Scientist / Machine Learning Engineer to build advanced analytics and Generative AI (Gen AI) solutions across multiple business functions. This role combines strong data analysis capabilities with machine learning and emerging Gen AI techniques to drive business insights, automation, and innovation. The ideal candidate is hands-on, analytical, and comfortable owning the full lifecycle of data science solutions-from problem definition through model development and deployment-while collaborating closely with engineering and business stakeholders

Key Responsibilities Perform in-depth data analysis and exploration using SQL and statistical techniques to uncover patterns, solve business problems, and support data-driven decision-making. Work with large, complex datasets while ensuring data quality, integrity, and usability. Design, develop, and implement scalable solutions using Python or Java.

Utilize data science and machine learning libraries such as NumPy, SciPy, Matplotlib, and Scikit-learn. Build reusable pipelines for data processing, feature engineering, and model evaluation. Develop and evaluate machine learning models, including tree-based and ensemble algorithms such as Random Forest and XGBoost.

Assess model performance, tune hyperparameters, and ensure models meet business and technical requirements. Apply AI-assisted techniques to enhance productivity and insights. Craft effective prompts using Gemini or similar generative AI models to support data exploration, feature generation, analysis, and summarization.

Communicate insights through visualizations, reports, and presentations. Translate complex technical findings into actionable business recommendations. Partner closely with engineering teams for implementation and business stakeholders to ensure alignment with strategic objectives.

Required Qualifications Strong SQL and data analysis skills. Experience working with structured and semi-structured datasets. Proficiency in Python or Java for data science, machine learning, and analytical workloads.

Hands-on experience with machine learning frameworks and model development. Experience building, training, and evaluating predictive models in production or near-production environments. Ability to work independently and own initiatives end-to-end, from problem definition and requirements gathering through solution delivery and validation.

Experience using generative AI models to augment analytical workflows. Familiarity with prompt engineering. Experience leveraging large language models (LLMs) for automation and analytical tasks.

Experience integrating Gen AI capabilities into analytical processes. Generative AI Focus Develop and deploy Gen AI solutions that enhance productivity, automate workflows, and generate AI-driven business insights. Apply foundational knowledge of Gen AI concepts, tools, and use cases.

Experience with large language models (LLMs), prompt engineering, or AI-assisted analytics. Strong interest in emerging AI technologies and a willingness to continuously learn and apply new Gen AI innovations. Preferred Qualifications Experience working in financial services, banking, or capital markets environments.

Experience in data-driven or risk-focused domains. Familiarity with cloud platforms. Experience with data engineering pipelines.

Familiarity with model deployment frameworks. Exposure to big data technologies. Experience with distributed computing environments.

Exposure to real-time analytics environments. Ideal Candidate Profile Self-driven data professional with strong analytical and problem-solving skills. Combines practical machine learning expertise with emerging AI capabilities.

Comfortable navigating ambiguous problems and translating business needs into technical solutions. Capable of delivering measurable business outcomes. Strong communication skills with both technical and non-technical stakeholders.

Passionate about applying traditional machine learning and modern Generative AI techniques to solve complex business challenges.