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Remote Bioinformatics Machine Learning Jobs in North Carolina

Sunergi Inc

$110K - $140K/yr

Machine Learning EngineerFull-time We are expanding rapidly and are seeking new, experienced and hands-on team members who think outside of the box (and are not afraid to share their thoughts), will ...

LuckyJay Consulting

Bonus: knowledge of machine learning models and-development cycle * Experience with NGS data and bioinformatics tools and file formats * Bonus: Experience with multi-modal datasets Employment Type ...

Cigna

Data Science Director - Remote

Raleigh, NC · On-site +1

Provide technical leadership across machine learning, statistical modeling, feature engineering, model evaluation, calibration, explainability, and production-ready analytics. * Drive execution ...

LexisNexis

Director, Data Sciences

Raleigh, NC · On-site +1

... 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 ...

LexisNexis

Director, Data Sciences

Raleigh, NC · On-site +1

... 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 Bioinformatics Machine Learning information

How do remote bioinformatics machine learning professionals typically collaborate with cross-functional teams?

Remote bioinformatics machine learning professionals often work closely with biologists, data scientists, and software engineers. Collaboration is typically facilitated through virtual meetings, shared code repositories, and project management tools. Regular communication is essential to align on data requirements, model development, and interpretation of results. While remote work offers flexibility, it requires strong organizational skills and proactive engagement to ensure seamless teamwork and project success.

What is a Remote Bioinformatics Machine Learning specialist?

A Remote Bioinformatics Machine Learning specialist is a professional who applies machine learning techniques to biological data, such as genomics or proteomics, while working from a remote location. They analyze complex biological datasets to uncover patterns, make predictions, and contribute to advancements in areas like drug discovery, disease research, and personalized medicine. These specialists typically have strong skills in programming, statistics, biology, and data analysis, and collaborate with researchers and healthcare professionals through digital communication tools.

What are the key skills and qualifications needed to thrive as a Remote Bioinformatics Machine Learning Specialist, and why are they important?

To excel as a Remote Bioinformatics Machine Learning Specialist, a strong background in computational biology, statistics, and machine learning—often supported by an advanced degree in bioinformatics, computer science, or a related field—is essential. Proficiency with programming languages like Python or R, experience using machine learning frameworks (such as TensorFlow or scikit-learn), and familiarity with bioinformatics tools and databases are typically required. Excellent problem-solving, self-motivation, and clear communication skills help professionals collaborate effectively and independently in remote environments. These abilities are vital for developing accurate models, interpreting complex biological data, and contributing meaningful insights to scientific research.

What is the difference between Remote Bioinformatics Machine Learning vs Remote Computational Biologist?

AspectRemote Bioinformatics Machine LearningRemote Computational Biologist
Required CredentialsMaster's or PhD in Bioinformatics, Computer Science, or related fields; experience in machine learningMaster's or PhD in Biology, Bioinformatics, or related fields; strong computational skills
Work EnvironmentRemote, collaborative teams in biotech, pharma, or research institutionsRemote or on-site, working in research labs or academic settings
Industry UsageUsed in biotech, healthcare, and pharmaceutical industries for data analysis and model developmentCommon in academic research, biotech, and healthcare for biological data interpretation

Remote Bioinformatics Machine Learning focuses on developing algorithms and models to analyze biological data using machine learning techniques. In contrast, Remote Computational Biologist applies computational methods to biological research questions, often integrating diverse data types. Both roles require strong computational skills and often overlap, but the former emphasizes machine learning expertise, while the latter has a broader biological research scope.

What are the most commonly searched types of Bioinformatics Machine Learning jobs in North Carolina? The most popular types of Bioinformatics Machine Learning jobs in North Carolina are:
What are popular job titles related to Remote Bioinformatics Machine Learning jobs in North Carolina? For Remote Bioinformatics Machine Learning jobs in North Carolina, the most frequently searched job titles are:
What job categories do people searching Remote Bioinformatics Machine Learning jobs in North Carolina look for? The top searched job categories for Remote Bioinformatics Machine Learning jobs in North Carolina are:
What cities in North Carolina are hiring for Remote Bioinformatics Machine Learning jobs? Cities in North Carolina with the most Remote Bioinformatics Machine Learning job openings:
Remote Bioinformatics Machine Learning jobs near you
Machine Learning Engineer (Remote)

Machine Learning Engineer (Remote)

Sunergi Inc

Remote

$110K - $140K/yr

Full-time

Posted 21 days ago

Job description

Sunergi Inc.Machine Learning EngineerFull-time


We are expanding rapidly and are seeking new, experienced and hands-on team members who think outside of the box (and are not afraid to share their thoughts), will deliver unique ideas and like to work in a fast-paced environment on cutting edge projects.


Our missionWe aim to map the best plots for solar panels in the United States.



The Machine Learning Engineer role is all about building, recruiting, management, internal communication and delivery - getting the product out the door, while ensuring the team is hitting their mark. Furthermore, the role will help to grow the engineering team, establish the engineering culture and remove impediments to help team members be able to provide their best.
Key Qualifications
  • You are a core contributor on ML projects with a focus on data ingestion, transformation and presentation for ML apps and reporting.
  • Passionate and dedicated track record of designing and implementing scalable, performant data pipelines, data services, and data products.
  • This is a hands-on position, expect to write more code.
  • Proficiency in at least one programming language (Java, Python or Scala) and a tried understanding of SQL.
  • Previous experience of dealing with multivariate data at petabyte scale, especially in the time-series domain.
  • Be able to communicate collaboratively with Data Scientists and ML Software developers to understand requirements we have and deliver best in class data platform.
  • Previous experience with statistical modeling and deep learning frameworks / libraries we use is required.
  • Strong aptitude for learning new technologies related to Data Management and Data Science.
  • Proven record to create and perform independently and within a fast-paced, team-oriented environment.
  • Work with structured and unstructured data. Perform data cleansing, scraping unstructured data and converting into structured data.
  • Evaluate, benchmark and improve the scalability, robustness, efficiency and performance of big data platform and applications.
  • Experience with Kubernetes, Docker is a plus
Description

In this role, handle implementing data pipelines focused on Machine Learning applications. 


  • You will develop data sets for POCs to demonstrate new insights. 
  • Several of these may lead to fully operational ML models and deploy and own the life-cycle on in-house and third party cloud environments. 
  • You will partner with various cross functional teams to define, develop and implement data technology solutions, with an emphasis on providing superior foundational data for ML applications. 
  • A strong understanding of distributed data systems and experience in using open source frameworks to build applications is required. 
  • A solid understanding of Deep learning platforms such as Keras, Tensor-flow and/or PyTorch is highly desirable, as is an ability to deploy solutions based on these platforms. 
  • Leveraging GPU & CPU resources as appropriate / understanding capacity requirements for ML Workloads, and working with partner teams to ensure scalability, business continuity and appropriate turnaround time is a key part of the operationalization effort. 
  • As a member of the team, you will be expected to take ownership of individual platform components and help set the vision and architecture for those. 
  • In the process, you will identify the requirements of new features, and propose design and drive the solution. 
  • A strong understanding of data governance and data privacy is expected for this role in keeping with Apple's strong commitment to the same.
Education & Experience

B.S or M.S in Computer Science, Mathematics, Statistics, Operational Research, Data Science / equivalent experience.

Additional Requirements
  • 3+ years of proven experience with Kubernetes, Docker is a plus

Compensation

  • 0.25% company equity, with vesting options up to 2%.
  • A strong, competitive salary upon reaching a seed round of funding. In the range of $110k-$140k/ year.



Employment Type: FULL_TIME

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