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Phd Machine Learning Startup Jobs in Michigan (NOW HIRING)

MS. or PhD in Machine Learning, or related field * Extensive AWS or GCP experience putting scalable Machine Learning systems into production. * Experience working with extremely high volume / high ...

Machine Learning-Gen Ai

Warren, MI · On-site +1

$107.30K - $128.80K/yr

A Master's or PhD in Mechanical Engineering, Industrial Engineering, or a related manufacturing-aligned discipline is required. Experience: A minimum of 3 years of experience in machine learning is ...

... PhD with 3 years experience * Prior success in deploying impactful Machine Learning solutions to ... large-scale production systems, while partnering across teams * Solid knowledge of data structures ...

... PhD with 3 years experience * Prior success in deploying impactful Machine Learning solutions to ... large-scale production systems, while partnering across teams * Solid knowledge of data structures ...

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Phd Machine Learning Startup information

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 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 job categories do people searching Phd Machine Learning Startup jobs in Michigan look for? The top searched job categories for Phd Machine Learning Startup jobs in Michigan are:
What cities in Michigan are hiring for Phd Machine Learning Startup jobs? Cities in Michigan with the most Phd Machine Learning Startup job openings:
Machine Learning Engineer

Machine Learning Engineer

Eccalon LLC

Detroit, MI

Full-time

Posted 4 days ago


Job description

Job Description

The Machine Learning Engineer will be an essential member of the Research and Development Team, where we engineer large tailor-made systems to solve complex data-related problems from many domains. At Eccalon, the projects we support often require solutions that utilize the latest and the best from Deep Learning/Machine Learning research. We support advanced projects in both data constrained and data rich settings. Qualified candidates should be driven and be able to help craft these systems as a part of our R&D team.

Responsibilities

  • Candidates are expected to be familiar with the motions of a classical Machine Learning workflow, and support the team with some of the following tasks:
    • Dataset Creation.
    • Data Exploration/Visualization.
    • Literature Review.
    • Data Wrangling.
    • Implementation and Training of Appropriate Models from Literature.
    • Characterization of Error in Models.
    • Iterative Optimization of Models.
  • On the engineering side of development, the Machine Learning Engineer will have the ability to be hands-on by:
    • Creating training and preprocessing pipelines for faster experimentation.
    • Creating algorithmic modules to interface your Models output with business requirements.
    • Integrating their code to a larger codebase.
    • Putting your model into production using AWS or GCP.

Required Qualifications

  • BS. in Computer Science, or related field.
  • 3+ years of professional Software Development experience in Python.
  • Mastery of Deep Learning fundamentals and statistics underlying Machine Learning.
  • History of software projects putting Machine Learning systems into production in any capacity.
  • History of software projects in general.
  • Deep personal interest with the complete state of the art in a subfield of Machine Learning Research.
  • Ability to work independently, and within a team.
  • Ability to communicate effectively with non-technical stakeholders and supervisors.
  • Prior project experience combining two or more of the following in a production setting:
    • Unsupervised or Semi-supervised Learning.
    • Convolutional Architectures.
    • Autoencoders.
    • Recurrent Architectures for Time-Series Applications.
    • Transformer Architectures for Natural Language Processing.
    • Generative Adversarial Architectures.

Preferred qualifications

  • MS. or PhD in Machine Learning, or related field
  • Extensive AWS or GCP experience putting scalable Machine Learning systems into production.
  • Experience working with extremely high volume / high throughput data in a data lake / data warehousing / training / production environment.
  • Has implemented cutting edge methods (e.g. a custom layer) from recent Machine Learning publications / conference proceedings and has done so in PyTorch or Tensorflow.
  • Publications in AI/ML journals or conferences.

Equal Employment Opportunity (EEO) Policy

Eccalon provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.


Eccalon logo

About Eccalon

Sourced by ZipRecruiter

We are a cross-functional collective of innovative minds that leverages technology to tackle the most challenging problems of this generation for clients, the nation, and the world. Eccalon fosters creativity, curiosity, and imagination across all departments and divisions to pioneer new ideas, products, and services. We advance innovation.​

Industry

Guided missile and space vehicle manufacturing

Company size

11 - 50 Employees

Headquarters location

Hanover, MD, US

Year founded

2017