Preferred : • Master's degree or PhD in Machine Learning or related field • At least one year of hands-on experience applying machine learning principles and algorithms involving embedded systems ...
Preferred : • Master's degree or PhD in Machine Learning or related field • At least one year of hands-on experience applying machine learning principles and algorithms involving embedded systems ...
Preferred : • Master's degree or PhD in Machine Learning or related field • At least one year of hands-on experience applying machine learning principles and algorithms involving embedded systems ...
Preferred : • Master's degree or PhD in Machine Learning or related field • At least one year of hands-on experience applying machine learning principles and algorithms involving embedded systems ...
We use machine learning and Internet-scale data to elevate customer experience, improve efficiency, and reduce cost. As an example, we manage catalog data imported from hundreds of retailers, and we ...
We use machine learning and Internet-scale data to elevate customer experience, improve efficiency, and reduce cost. As an example, we manage catalog data imported from hundreds of retailers, and we ...
We use machine learning and Internet-scale data to elevate customer experience, improve efficiency, and reduce cost. As an example, we manage catalog data imported from hundreds of retailers, and we ...
We use machine learning and Internet-scale data to elevate customer experience, improve efficiency, and reduce cost. As an example, we manage catalog data imported from hundreds of retailers, and we ...
We use machine learning and Internet-scale data to elevate customer experience, improve efficiency, and reduce cost. As an example, we manage catalog data imported from hundreds of retailers, and we ...
We use machine learning and Internet-scale data to elevate customer experience, improve efficiency, and reduce cost. As an example, we manage catalog data imported from hundreds of retailers, and we ...
We use machine learning and Internet-scale data to elevate customer experience, improve efficiency, and reduce cost. As an example, we manage catalog data imported from hundreds of retailers, and we ...
We use machine learning and Internet-scale data to elevate customer experience, improve efficiency, and reduce cost. As an example, we manage catalog data imported from hundreds of retailers, and we ...
We use machine learning and Internet-scale data to elevate customer experience, improve efficiency, and reduce cost. As an example, we manage catalog data imported from hundreds of retailers, and we ...
We use machine learning and Internet-scale data to elevate customer experience, improve efficiency, and reduce cost. As an example, we manage catalog data imported from hundreds of retailers, and we ...
We use machine learning and Internet-scale data to elevate customer experience, improve efficiency, and reduce cost. As an example, we manage catalog data imported from hundreds of retailers, and we ...
We use machine learning and Internet-scale data to elevate customer experience, improve efficiency, and reduce cost. As an example, we manage catalog data imported from hundreds of retailers, and we ...
We use machine learning and Internet-scale data to elevate customer experience, improve efficiency, and reduce cost. As an example, we manage catalog data imported from hundreds of retailers, and we ...
We use machine learning and Internet-scale data to elevate customer experience, improve efficiency, and reduce cost. As an example, we manage catalog data imported from hundreds of retailers, and we ...
Preferred : • Master's degree or PhD in Machine Learning or related field is preferred • At least three years of hands-on experience applying machine learning principles and algorithms involving ...
Preferred : • Master's degree or PhD in Machine Learning or related field is preferred • At least three years of hands-on experience applying machine learning principles and algorithms involving ...
Preferred : • Master's degree or PhD in Machine Learning or related field is preferred • At least three years of hands-on experience applying machine learning principles and algorithms involving ...
Preferred : • Master's degree or PhD in Machine Learning or related field is preferred • At least three years of hands-on experience applying machine learning principles and algorithms involving ...
Master's degree or PhD in Machine Learning or related field * At least one year of hands-on experience applying machine learning principles and algorithms involving embedded systems, edge computing ...
Master's degree or PhD in Machine Learning or related field * At least one year of hands-on experience applying machine learning principles and algorithms involving embedded systems, edge computing ...
Master's degree or PhD in Machine Learning or related field * At least one year of hands-on experience applying machine learning principles and algorithms involving embedded systems, edge computing ...
Master's degree or PhD in Machine Learning or related field * At least one year of hands-on experience applying machine learning principles and algorithms involving embedded systems, edge computing ...
Master's degree or PhD in Machine Learning or related field * At least one year of hands-on experience applying machine learning principles and algorithms involving embedded systems, edge computing ...
Master's degree or PhD in Machine Learning or related field * At least one year of hands-on experience applying machine learning principles and algorithms involving embedded systems, edge computing ...
Master's degree or PhD in Machine Learning or related field is preferred * At least three years of hands-on experience applying machine learning principles and algorithms involving embedded systems ...
Master's degree or PhD in Machine Learning or related field is preferred * At least three years of hands-on experience applying machine learning principles and algorithms involving embedded systems ...
Master's degree or PhD in Machine Learning or related field is preferred * At least three years of hands-on experience applying machine learning principles and algorithms involving embedded systems ...
Master's degree or PhD in Machine Learning or related field is preferred * At least three years of hands-on experience applying machine learning principles and algorithms involving embedded systems ...
Master's degree or PhD in Machine Learning or related field is preferred * At least three years of hands-on experience applying machine learning principles and algorithms involving embedded systems ...
Master's degree or PhD in Machine Learning or related field is preferred * At least three years of hands-on experience applying machine learning principles and algorithms involving embedded systems ...
$225K - $260K/yr
Master's or PhD in Computer Science, Robotics, Electrical Engineering, Machine Learning, or a closely related technical discipline. * Minimum of 5 years of professional experience developing ...
$225K - $260K/yr
Master's or PhD in Computer Science, Robotics, Electrical Engineering, Machine Learning, or a closely related technical discipline. * Minimum of 5 years of professional experience developing ...
Have a graduate degree (masters or PhD) in artificial intelligence, machine learning, operations research or equivalent self study and experience * Have strong programming skills in Python and ...
Have a graduate degree (masters or PhD) in artificial intelligence, machine learning, operations research or equivalent self study and experience * Have strong programming skills in Python and ...
Have a graduate degree (masters or PhD) in artificial intelligence, machine learning, operations research or equivalent self study and experience * Have strong programming skills in Python and ...
Have a graduate degree (masters or PhD) in artificial intelligence, machine learning, operations research or equivalent self study and experience * Have strong programming skills in Python and ...
Phd Machine Learning Startup information
What are some common challenges faced by PhD-level professionals working in machine learning startups?
PhD-level professionals in machine learning startups often encounter challenges such as balancing research innovation with the need for rapid product development. Unlike academia, startups prioritize practical solutions that fit tight deadlines and resource constraints. Team members typically wear multiple hats and collaborate closely with engineers, product managers, and business stakeholders, requiring strong communication skills and adaptability. Additionally, translating cutting-edge research into scalable, real-world applications can be both intellectually rewarding and demanding.
What do PhD holders in Machine Learning do at startups?
PhD holders in Machine Learning at startups typically lead research and development efforts to create innovative algorithms and models that solve real-world problems. They often work on designing and implementing advanced machine learning solutions, analyzing large datasets, and collaborating with product and engineering teams to bring research ideas to production. Their expertise helps startups stay competitive by driving technological advancements and fostering a culture of innovation.
What are the key skills and qualifications needed to thrive as a PhD-level Machine Learning professional in a startup environment, and why are they important?
To excel as a PhD-level Machine Learning professional at a startup, you need advanced expertise in machine learning algorithms, statistical modeling, and a doctoral degree in a related field. Experience with Python, TensorFlow, PyTorch, and version control systems, along with a strong publication record, is typically expected. Initiative, adaptability, and excellent problem-solving and communication abilities are crucial soft skills in the fast-paced startup setting. These competencies enable rapid innovation, effective team collaboration, and successful deployment of machine learning solutions under resource constraints.
What are popular job titles related to Phd Machine Learning Startup jobs in Wisconsin? For Phd Machine Learning Startup jobs in Wisconsin, the most frequently searched job titles are:
What job categories do people searching Phd Machine Learning Startup jobs in Wisconsin look for? The top searched job categories for Phd Machine Learning Startup jobs in Wisconsin are:
What cities in Wisconsin are hiring for Phd Machine Learning Startup jobs? Cities in Wisconsin with the most Phd Machine Learning Startup job openings:
Job description
Job Summary:
Techtronic Industries - TTI is committed to innovation and excellence in engineering, particularly in the realm of power tools. As a Machine Learning Engineer I, you will lead the deployment of machine learning models, collaborating with cross-functional teams to enhance product development and implementation. This role emphasizes problem-solving, technical communication, and project management to drive initiatives that improve user experiences.
Responsibilities:
• Deploy machine learning models in creative ways while working with cross-functional teams.
• Act as a technical expert in the creation and execution of concepts into products.
• Support the team through implementation, validation, and transfer to production.
• Leverage strong technical communication skills and project management abilities to ensure clarity and alignment across teams.
• Demonstrate a strong sense of ownership for projects and tasks, understanding their connection to broader initiatives.
Qualifications:
Required:
• Bachelor of Science Degree in Computer Science, Computer Engineering, Electrical Engineering or other scientific or engineering discipline.
• Completed course work or specialization in Machine Learning and/or Data Science
• Demonstrated experience applying fundamental machine learning algorithms and techniques in a non-coursework setting (e.g. unsupervised or supervised learning, classification/regression, dimensionality reduction, model optimization)
• Demonstrated experience with machine learning and AI methods such as CNNS, transformers, or computer vision
• Proficient developing and debugging code in Python
• Proficiency in Python, with extensive experience in common libraries (NumPy, pandas, scikit-learn, Matplotlib, etc.)
• Proficiency with at least one deep learning framework (e.g. PyTorch of Tensor Flow)
• Sold mathematical foundation in statistics, linear algebra, calculus and optimization
• Ability to travel up to 10% of the time (domestic and international).
Preferred:
• Master’s degree or PhD in Machine Learning or related field
• At least one year of hands-on experience applying machine learning principles and algorithms involving embedded systems, edge computing, signal processing or a related field are preferred
• Experience with time series modelling, especially with related domains such as NLP, SLAM, forecasting, or audio/video processing
• Proficient developing and debugging code in an embedded environment in a programming language such as C or C++
• Experience working with modern software development tools and version control tools
Company:
Milwaukee Tool manufactures electric power tools and accessories. Founded in 1924, the company is headquartered in Brookfield, USA, with a team of 5001-10000 employees. The company is currently .
Techtronic Industries - TTI is committed to innovation and excellence in engineering, particularly in the realm of power tools. As a Machine Learning Engineer I, you will lead the deployment of machine learning models, collaborating with cross-functional teams to enhance product development and implementation. This role emphasizes problem-solving, technical communication, and project management to drive initiatives that improve user experiences.
Responsibilities:
• Deploy machine learning models in creative ways while working with cross-functional teams.
• Act as a technical expert in the creation and execution of concepts into products.
• Support the team through implementation, validation, and transfer to production.
• Leverage strong technical communication skills and project management abilities to ensure clarity and alignment across teams.
• Demonstrate a strong sense of ownership for projects and tasks, understanding their connection to broader initiatives.
Qualifications:
Required:
• Bachelor of Science Degree in Computer Science, Computer Engineering, Electrical Engineering or other scientific or engineering discipline.
• Completed course work or specialization in Machine Learning and/or Data Science
• Demonstrated experience applying fundamental machine learning algorithms and techniques in a non-coursework setting (e.g. unsupervised or supervised learning, classification/regression, dimensionality reduction, model optimization)
• Demonstrated experience with machine learning and AI methods such as CNNS, transformers, or computer vision
• Proficient developing and debugging code in Python
• Proficiency in Python, with extensive experience in common libraries (NumPy, pandas, scikit-learn, Matplotlib, etc.)
• Proficiency with at least one deep learning framework (e.g. PyTorch of Tensor Flow)
• Sold mathematical foundation in statistics, linear algebra, calculus and optimization
• Ability to travel up to 10% of the time (domestic and international).
Preferred:
• Master’s degree or PhD in Machine Learning or related field
• At least one year of hands-on experience applying machine learning principles and algorithms involving embedded systems, edge computing, signal processing or a related field are preferred
• Experience with time series modelling, especially with related domains such as NLP, SLAM, forecasting, or audio/video processing
• Proficient developing and debugging code in an embedded environment in a programming language such as C or C++
• Experience working with modern software development tools and version control tools
Company:
Milwaukee Tool manufactures electric power tools and accessories. Founded in 1924, the company is headquartered in Brookfield, USA, with a team of 5001-10000 employees. The company is currently .