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Remote Co Op Computer Science Jobs (NOW HIRING)

Tamr

Marketing Co-Op 2026 (H2)

Cambridge, MA · Remote

$30 - $35/hr

Access to a computer with an internet connection is required. Applicants must be currently pursuing ... Applicants should be available for co-op from August 2026 to December 2026. This position is hybrid ...

TPAPT

AP Computer Science Tutor (Remote)

New York, NY · Remote

$30 - $35/hr

... Computer Science instructors to work with students in grades 9-12. Tutors will work closely with ... A passion for helping others learn Benefits * $30-$35/hr. commensurate * 100% remote * Flexible ...

TPAPT

AP Computer Science Tutor (Remote)

Boston, MA · Remote

$30 - $35/hr

... Computer Science instructors to work with students in grades 9-12. Tutors will work closely with ... A passion for helping others learn Benefits * $30-$35/hr. commensurate * 100% remote * Flexible ...

TPAPT

AP Computer Science Tutor (Remote)

Los Angeles, CA · Remote

$30 - $35/hr

... Computer Science instructors to work with students in grades 9-12. Tutors will work closely with ... A passion for helping others learn Benefits * $30-$35/hr. commensurate * 100% remote * Flexible ...

Waabi

Research Internship/Co-op

San Francisco, CA · On-site +1

$45 - $60/hr

Qualifications: - Bachelors or MS/PhD degree in Computer Science, Engineering, AI, Machine Learning ... Application Instructions: - To be considered for an internship/co-op, please add your most up to ...

Stride, Inc.

Computer Science CTE Teacher

Denton, TX · Remote

$49K/yr

TEXAS The remote High School CTE Teacher in Computer Science is state certified teacher and/or alternatively certified CRE/CTE Teacher responsible for delivering specific course content in an on-line ...

Lehigh University

$67K - $90K/yr

Bethlehem, Fully Remote Categories: Student Life Director of Internships and Employer Partnerships ... Design and scale high-impact internship and co-op opportunities by analyzing workforce trends and ...

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All JobsRemote Co Op Computer Science Jobs

Remote Co Op Computer Science information

How do Remote Co-Op Computer Science roles typically facilitate mentorship and team collaboration despite the virtual setting?

Remote Co-Op Computer Science positions often leverage various collaboration tools such as Slack, Microsoft Teams, and Zoom to foster communication and mentorship. You'll participate in regular virtual stand-ups, code reviews, and project meetings, ensuring you stay connected with your team and receive guidance from senior engineers. Many companies assign a dedicated mentor or buddy to help you navigate both technical challenges and company culture. This structure allows you to build relationships, gain feedback, and make meaningful contributions without being onsite.

What is a Remote Co-Op in Computer Science?

A Remote Co-Op in Computer Science is a paid or unpaid work placement that allows students to gain real-world experience in their field while working from a location outside the traditional office, such as their home. These positions are typically part of a college or university's cooperative education program, blending academic learning with practical work experience. Students work on software development, data analysis, or IT projects under the supervision of professionals, helping them build technical skills and professional networks. Remote Co-Ops offer flexibility and can connect students with companies outside their local area, broadening their career opportunities.

What are the key skills and qualifications needed to thrive as a Remote Co-Op Computer Science student, and why are they important?

To thrive as a Remote Co-Op Computer Science student, you need a solid grasp of programming fundamentals, data structures, algorithms, and typically be pursuing or have completed coursework toward a computer science degree. Familiarity with version control systems like Git, collaborative platforms such as GitHub or Jira, and exposure to coding languages like Python, Java, or C++ are commonly expected. Strong communication, self-motivation, and time management are essential soft skills for remote teamwork and independent learning. These skills ensure you can effectively contribute to projects, adapt to remote workflows, and maximize your experiential learning.

What is the difference between Remote Co Op Computer Science vs Remote Software Intern?

AspectRemote Co Op Computer ScienceRemote Software Intern
CredentialsTypically enrolled in a computer science program, may require coursework or enrollment verificationUsually students pursuing a degree in computer science or related field, may need proof of enrollment
Work EnvironmentRemote, collaborative team settings, often part-time during academic termsRemote, project-based tasks, often part-time or summer internships
Employer & Industry UsageUsed by tech companies, startups, and corporations for student talent pipelinesCommonly offered by tech firms, startups, and software companies for skill development

Both roles are designed for students gaining practical experience in computer science. The main difference lies in the stage of education and the program structure: Co Op positions are typically part of a formal cooperative education program, while Software Internships are often summer or short-term roles. Both provide valuable industry exposure and skill development in remote settings.

More about Remote Co Op Computer Science jobs
What cities are hiring for Remote Co Op Computer Science jobs? Cities with the most Remote Co Op Computer Science job openings:
What are the most commonly searched types of Remote Computer Science jobs? The most popular types of Remote Computer Science jobs are:
What states have the most Remote Co Op Computer Science jobs? States with the most job openings for Remote Co Op Computer Science jobs include:
What job categories do people searching Remote Co Op Computer Science jobs look for? The top searched job categories for Remote Co Op Computer Science jobs are:
Remote Co Op Computer Science jobs near you
Infographic showing various Remote Co Op Computer Science job openings in the United States as of June 2026, with employment types broken down into 67% Full Time, and 33% Part Time. Highlights an 100% Remote job distribution.
Data Science - AI Document Understanding, Co-op

Data Science - AI Document Understanding, Co-op

Ancestry

Remote

Part-time

Posted 16 days ago

Job description

About Ancestry:
When you join Ancestry, you join a human-centered company where every person's story is important. Ancestry®, the global leader in family history, connects everyone with their past so they can discover, preserve, and share their unique family stories. With our unparalleled collection of more than 65 billion records, over 3.5 million subscribers, and over 27 million people in our growing DNA network, customers can discover their family story and gain a new level of understanding about their lives. Over the past 40 years, we've built trusted relationships with millions of people who have chosen us as the platform for discovering, preserving, and sharing the most important information about themselves and their families.
We are committed to our location flexible work approach, allowing you to choose to work in the nearest office, from your home, or a hybrid of both (subject to location restrictions and roles that are required to be in the office- see the full list of eligible US locations HERE). We will continue to hire and promote beyond the boundaries of our office locations, to enable broadened possibilities for employee diversity.
Together, we work every day to foster a work environment that's inclusive as well as diverse, and where our people can be themselves. Every idea and perspective is valued so that our products and services reflect the global and diverse clients we serve.
Ancestry encourages applications from minorities, women, the disabled, protected veterans and all other qualified applicants. Passionate about dedicating your work to enriching people's lives? Join the curious.
Ancestry is seeking an exceptional and highly motivated AI Engineer / Data Science Co-op to join our AI Applied Science Content team. You'll play a vital role in the design and implementation of AI Native agentic systems that extract and organize text and image information from billions of historical and genealogical records, enabling customers to discover, share, and connect with their family history. The work will focus on building autonomous, multi-agent workflows capable of complex reasoning, tool use, analysis, and self-correction. You will also work closely with engineering teams to train, optimize, and deploy solutions that promote product development, customer success, and content creation across our Family History business. This is a part-time, work-study-based opportunity designed for active master's and PhD students continuing their education in the fall.
What you will do:
  • Innovate with State-of-the-Art AI: Implement cutting-edge AI solutions for key Document Understanding tasks such as OCR/HTR, transcription, Named Entity Recognition (NER), Relation Extraction (RE), Coreference Resolution, Summarization, and Knowledge Graphs working with diverse genealogical and historical collections spanning newspapers, city directories, family history books, and vital records (i.e., birth, marriage, & death records).
  • Analyze and Optimize Multi-Modal Models: Evaluate the performance of multi-modal models in zero-shot and few-shot learning scenarios for comprehensive document understanding.
  • Architect Agentic Systems: Design and implement multi-agent workflows using frameworks like LangChain, LangGraph, CrewAI, or AutoGen to automate complex multi-step reasoning tasks in historical document analysis.
  • Evaluation & Observability: Establish "LLM-as-a-Judge" frameworks and use tools like Arize Phoenix, DeepEval, or RAGAS to monitor for hallucination, drift, and bias.
  • Collaborate on Cloud Deployment: Partner closely with ML Ops and Data Science Engineers to seamlessly deploy datasets, models, and pipelines in cloud environments.
  • Communicate Insights Effectively: Clearly and confidently present your findings, deliverables, and proposed solutions to technical and non-technical audiences, including teams, stakeholders, and executives.

Who You Are:
  • Currently pursuing an advanced degree (Master's or PhD preferred) in Computer Science, Data Science, Statistics, Mathematics, Linguistics, Engineering or related quantitative field with a strong data focus.
  • Specialization in AI & LLMs including familiarity with foundational models such as GPT, Gemini, Qwen, Llama, Claude, etc.
  • Experience with inference optimization, vLLM, LoRA, QLoRA, quantization, etc.
  • Familiar with embeddings, vector databases, transformer models, with software development experience.
  • Strong proficiency in Python and relevant tools and libraries, including transformer models, multi-modal models, and general NLP (e.g., Hugging Face Transformers, agentic frameworks andworkflows, LangChain, LangGraph, CrewAI, AgentCore).
  • Familiarity with cloud platforms and related AI/ML services such as Google Cloud Platform, GCP, Gemini API, Vertex AI, AWS EC2, S3, SageMaker, Model Registry, and Bedrock is a plus.

Additional Information:
Ancestry is an Equal Opportunity Employer that makes employment decisions without regard to race, color, religious creed, national origin, ancestry, sex, pregnancy, sexual orientation, gender, gender identity, gender expression, age, mental or physical disability, medical condition, military or veteran status, citizenship, marital status, genetic information, or any other characteristic protected by applicable law. In addition, Ancestry will provide reasonable accommodations for qualified individuals with disabilities.
All job offers are contingent on a background check screen that complies with applicable law. For candidates who live in San Francisco, CA, pursuant to the San Francisco Fair Chance Ordinance, Ancestry will consider for employment qualified applicants with arrest and conviction records.
Ancestry is not accepting unsolicited assistance from search firms for this employment opportunity. All resumes submitted by search firms to any employee at Ancestry via-email, the Internet or in any form and/or method without a valid written search agreement in place for this position will be deemed the sole property of Ancestry. No fee will be paid in the event the candidate is hired by Ancestry as a result of the referral or through other means.

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