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Contract Machine Learning Startup Jobs in Baltimore, MD

Machine Learning Engineer

Annapolis Junction, MD ยท On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Some contracts give 2 years experience credit for a Master's Degree. We will work with you to find the right fit. POSITION RESPONSIBILITIES * Strong understanding of machine learning algorithms ...

Machine Learning Tutor

College Park, MD ยท Remote

$18 - $40/hr

What We Look For In a Machine Learning Tutor * Advanced Subject Mastery: Deep knowledge of ... Varsity Tutors does not contract in: Alaska, California, Colorado, Delaware, Hawaii, Maine, New ...

Machine Learning Tutor

Laurel, MD ยท Remote

$18 - $40/hr

What We Look For In a Machine Learning Tutor * Advanced Subject Mastery: Deep knowledge of ... Varsity Tutors does not contract in: Alaska, California, Colorado, Delaware, Hawaii, Maine, New ...

Machine Learning Tutor

Baltimore, MD ยท Remote

$18 - $40/hr

What We Look For In a Machine Learning Tutor * Advanced Subject Mastery: Deep knowledge of ... Varsity Tutors does not contract in: Alaska, California, Colorado, Delaware, Hawaii, Maine, New ...

Machine Learning Tutor

Bowie, MD ยท Remote

$18 - $40/hr

What We Look For In a Machine Learning Tutor * Advanced Subject Mastery: Deep knowledge of ... Varsity Tutors does not contract in: Alaska, California, Colorado, Delaware, Hawaii, Maine, New ...

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Contract Machine Learning Startup information

See Baltimore, MD salary details

$29

$48

$98

How much do contract machine learning startup jobs pay per hour?

As of Aug 18, 2026, the average hourly pay for contract machine learning startup in Baltimore, MD is $48.62, according to ZipRecruiter salary data. Most workers in this role earn between $40.87 and $50.38 per hour, depending on experience, location, and employer.

What is a contract machine learning startup?

A Contract Machine Learning Startup is a company or team that provides machine learning solutions and services to clients on a contract basis. Instead of developing their own products, these startups typically work with other businesses to build custom machine learning models, analyze data, and help integrate AI technologies into existing workflows. They may offer expertise in areas such as natural language processing, computer vision, or predictive analytics, and usually operate on short-term or project-based contracts. This approach allows client companies to access specialized knowledge without hiring full-time data scientists or engineers.

What are the key skills and qualifications needed to thrive in a contract machine learning startup role?

Success in a Contract Machine Learning Startup role generally requires expertise in machine learning algorithms, data analysis, and a solid background in computer science or related fields. Familiarity with programming languages such as Python or R, experience with ML frameworks like TensorFlow or PyTorch, and knowledge of cloud platforms (e.g., AWS, GCP) are typically expected. Strong problem-solving, adaptability, and effective communication help professionals collaborate with clients and respond to rapidly changing project requirements. These skills and qualities are vital to deliver innovative, scalable solutions in fast-paced, outcome-driven startup environments.

What are some common challenges faced by machine learning professionals working on a contract basis at startups?

Machine learning professionals working as contractors at startups often face challenges such as rapidly changing project scopes, limited access to large datasets, and the need to quickly adapt to new tools and frameworks. Startups typically move fast, so contractors must be comfortable with ambiguity and prioritize delivering value in short timeframes. Additionally, they may need to collaborate closely with cross-functional teams, such as product managers and engineers, to ensure that machine learning solutions align with business goals.

What is the difference between Contract Machine Learning Startup vs Data Scientist?

AspectContract Machine Learning StartupData Scientist
CredentialsRelevant degrees, certifications in ML/AITypically similar credentials, often with advanced degrees
Work EnvironmentProject-based, startup setting, flexible hoursOffice or remote, corporate or research settings
Employer & IndustryStartups in tech, AI, or data-driven sectorsVaried industries including tech, finance, healthcare
Search & Comparison IntentUnderstanding contract roles in ML startupsExploring data science career options

Contract Machine Learning Startup roles focus on short-term, project-based work within startup environments, often requiring specialized skills in ML and AI. Data Scientists typically work in more established companies or research settings, with similar credentials but often in a full-time capacity. Both roles demand strong technical backgrounds, but contract roles offer flexibility and varied projects, while Data Scientists may have more stability and broader responsibilities.

What are the most commonly searched types of Machine Learning Startup jobs in Baltimore, MD?

The most popular types of Machine Learning Startup jobs in Baltimore, MD are:

What are popular job titles related to Contract Machine Learning Startup jobs in Baltimore, MD?

For Contract Machine Learning Startup jobs in Baltimore, MD, the most frequently searched job titles are:

Machine Learning Engineer

Full Scope

Fort George G Meade, MD โ€ข On-site

$120 - $180/hr

Other

Posted 7 days ago


Job description

Job Title:Machine Learning Engineer

Location:Fort Meade, MD

Required Clearance: TS/SCI w/ Full-Scope Poly

Salary:Competitive

We are seeking a highly skilled and motivated Machine Learning Engineer to join our dynamic team. The ideal candidate will have a strong background in machine learning, data science, and software engineering. You will work closely with data scientists, engineers, and product managers to design, develop, and deploy machine learning models and solutions that drive business value.

Key Responsibilities
  • Design, develop, and implement machine learning models and algorithms to solve real-world problems.
  • Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.
  • Conduct data analysis and preprocessing to ensure high-quality data for model training.
  • Optimize and fine-tune models for performance, accuracy, and scalability.
  • Deploy machine learning models into production and monitor their performance.
  • Develop and maintain machine learning pipelines and infrastructure.
  • Stay current with the latest research and advancements in machine learning and AI.
  • Participate in code reviews, team meetings, and contribute to a collaborative development environment.
  • Document processes, models, and findings comprehensively.
Qualifications
  • Bachelorโ€™s or Masterโ€™s degree in Computer Science, Engineering, Mathematics, or a related field. Ph.D. is a plus.
  • Proven experience as a Machine Learning Engineer or in a similar role.
  • Strong proficiency in programming languages such as Python, R, or Java.
  • Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, Scikit-learn, etc.
  • Solid understanding of machine learning algorithms, including supervised and unsupervised learning, reinforcement learning, and deep learning.
  • Experience with data processing tools like Pandas, NumPy, and data visualization tools such as Matplotlib or Seaborn.
  • Familiarity with cloud platforms like AWS, Google Cloud, or Azure for model deployment and scaling.
  • Strong problem-solving skills and the ability to think critically and analytically.
  • Excellent communication and teamwork skills.
Preferred Qualifications
  • Experience with natural language processing (NLP) and computer vision.
  • Familiarity with big data technologies such as Hadoop, Spark, or Kafka.
  • Knowledge of software development best practices and version control systems like Git.
  • Experience with containerization tools like Docker and orchestration tools like Kubernetes.
  • Previous experience in a fast-paced, startup environment.
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