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Remote Algorithm Engineer Jobs (NOW HIRING)

GRVTY

Senior Scientist

Dayton, OH · Remote

$88K - $121K/yr

You will work alongside algorithm engineers, data scientists, and intelligence analysts to develop and apply physics-based models, image science methods, and multi-platform remote sensing analytics.

KBR, Inc.

GNC Engineer - Remote

$133K - $200K/yr

GNC Engineer - Remote Belong. Connect. Grow. with KBR! Around here, we define the future. We are a ... Support design, analysis, and verification of guidance, navigation, and control algorithms and ...

YO AI Labs

Backend Engineer - Remote

Dallas, TX · Remote

$80 - $120/hr

Remote Job Summary We are seeking experienced Senior Software Engineers to support an AI training ... Strong understanding of algorithms and data structures . * Experience with bug fixing and debugging ...

YO AI Labs

Backend Engineer - Remote

San Francisco, CA · Remote

$80 - $120/hr

Remote Job Summary We are seeking experienced Senior Software Engineers to support an AI training ... Strong understanding of algorithms and data structures . * Experience with bug fixing and debugging ...

KBR

GNC Engineer - Remote

$133K - $200K/yr

GNC Engineer - Remote Belong. Connect. Grow. with KBR! Around here, we define the future. We are a ... Support design, analysis, and verification of guidance, navigation, and control algorithms and ...

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Remote Algorithm Engineer information

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$59.5K

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How much do remote algorithm engineer jobs pay per year?

As of Sep 11, 2026, the average yearly pay for remote algorithm engineer in the United States is $111,632.00, according to ZipRecruiter salary data. Most workers in this role earn between $80,500.00 and $132,500.00 per year, depending on experience, location, and employer.

What is a remote algorithm engineer?

A Remote Algorithm Engineer is a professional who designs, develops, and optimizes algorithms for various applications, such as data analysis, machine learning, or software development, while working from a remote location. This role involves solving complex problems, collaborating with team members online, and implementing efficient solutions to improve system performance. Remote Algorithm Engineers often work in industries like technology, finance, healthcare, and more, utilizing programming languages and mathematical concepts to create effective algorithms.

What are the key skills and qualifications needed to thrive as a remote algorithm engineer?

To thrive as a Remote Algorithm Engineer, you need a strong background in computer science, mathematics, and algorithm design, often supported by a relevant degree. Proficiency in programming languages such as Python, C++, or Java, and experience with version control systems and cloud-based collaboration tools are typically required. Strong problem-solving abilities, self-motivation, and clear communication skills are essential for excelling in a remote environment. These skills ensure the engineer can develop efficient solutions, collaborate effectively with distributed teams, and deliver high-quality work independently.

What are some common challenges faced by remote algorithm engineers, and how can they be addressed?

Remote Algorithm Engineers often face challenges such as effective communication with distributed teams, managing their own schedules, and ensuring seamless integration of their work with larger systems. To address these, it's important to leverage collaborative tools (like code repositories, project management platforms, and video conferencing), maintain clear and regular communication with colleagues, and participate in code reviews and design discussions. Establishing a structured routine and proactively seeking feedback can also help in staying aligned with project goals and team expectations.
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Remote Algorithm Engineer jobs near you
Infographic showing various Remote Algorithm Engineer job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 87% Full Time, 9% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $111,632 per year, or $53.7 per hour.

Principal Scientist, Algorithm Lead

Remote

NeoGenomics Laboratories
Health Care and Social Assistance • 1 - 5K employees
Learn more about NeoGenomics Laboratoriesexternal

Full-time

Medical, Retirement, PTO

Re-posted 18 days ago

NeoGenomics rating

8.0

Company rating: 8.0 out of 10

Based on 34 frontline employees who took The Breakroom Quiz

Job description

Description
Are you motivated to participate in a dynamic, multi-tasking environment? Do you want to join a company that invests in its employees? Are you seeking a position where you can use your skills while continuing to be challenged and learn? Then we encourage you to dive deeper into this opportunity.
We believe in career development and empowering our employees. Not only do we provide career coaches internally, but we offer many training opportunities to expand your knowledge base! We have highly competitive benefits with a variety HMO and PPO options. We have company 401k match along with an Employee Stock Purchase Program. We have tuition reimbursement, leadership development, and even start employees off with 16 days of paid time off plus holidays. We offer wellness courses and have highly engaged employee resource groups. Come join the Neo team and be part of our amazing World Class Culture!
NeoGenomics is looking for a Principal Scientist Algorithm Lead - Clinical NGS Diagnostics who wants to learn to continue to learn in order to allow our company to grow. This is a remote position.
Now that you know what we're looking for in talent, let us tell you why you'd want to work at NeoGenomics:
As an employer, we promise to provide you with a purpose driven mission in which you have the opportunity to save lives by improving patient care through the exceptional work you perform. Together, we will become the world's leading cancer reference laboratory.
Position Summary:
As the Principal Scientist Algorithm Lead you will provide end-to-end scientific and technical leadership for clinical-grade NGS diagnostic algorithms, with a primary focus on oncology and liquid biopsy applications. This role owns algorithm design, analytical validation, design control, and regulatory readiness, with an emphasis on improving sensitivity, robustness, and reproducibility across complex variant classes.
Responsibilities:
  • Own the full lifecycle of clinical NGS algorithms under design control, including requirements definition, risk analysis, traceability to analytical claims, and design change impact assessment.
  • Architect and lead automated analytical validation frameworks spanning accuracy, precision, sensitivity/LOD, specificity, linearity, and robustness for SNVs, indels, CNVs, structural variants, gene fusions, and RNA-based assays.
  • Define algorithm-level error models, performance budgets, and acceptance criteria, driving systematic improvements in low-VAF detection, background suppression, and assay-specific artifact mitigation.
  • Establish statistically rigorous approaches for truth set construction, reference materials, in silico mixing, and synthetic data generation to support scalable and reproducible validation.
  • Serve as final technical authority on algorithm changes, including re-validation scope, documentation strategy, and regulatory impact.
  • Lead development and optimization of variant calling and signal extraction algorithms for DNA- and RNA-based assays, including ultra-deep sequencing and challenging genomic regions.
  • Develop and track NGS-based quality control metrics at the read, molecule, sample, and assay levels (e.g., coverage, uniformity, duplication/UMI yield, error rates, contamination, noise profiles) to monitor analytical performance and stability.
  • Apply probabilistic modeling, Bayesian inference, and machine learning to improve sensitivity and specificity while maintaining interpretability and regulatory defensibility.
  • Lead algorithm development for solid tumor and hematologic malignancy profiling, including tissue and liquid biopsy use cases.
  • Address challenges specific to low-input DNA/RNA, fragmented cfDNA, and ultra-low-allele-frequency variants.
  • Translate algorithm behavior and QC performance into clear, testable analytical claims aligned with CLIA, CAP, FDA, NYDoH, CLSI, and MolDx expectations.
  • Author and review algorithm components of validation reports, design history documentation, and regulatory submissions.

Education, Experience & Qualifications:
  • PhD in Bioinformatics, Computational Biology, Computer Science, Statistics, or a related quantitative field.
  • 8+ years of experience developing algorithms for clinical NGS diagnostics, ideally in oncology.
  • Deep expertise in SNV/indel, CNV, SV, fusion, and RNA analysis, NGS QC metrics, statistical modeling, and analytical performance evaluation.
  • Demonstrated leadership in analytical validation and regulatory submissions (CLIA, CAP, FDA, NYDoH, MolDx).
  • Hands-on experience applying AI/ML methods to NGS data or biomarker development.
  • Expert programming skills in Python and R; strong understanding of workflow orchestration and validation automation.
  • Strong publication or presentation record in computational genomics or NGS diagnostics.
  • Experience building QC-driven, highly automated validation pipelines with rigorous statistical controls.
  • Familiarity with payer evidence and reimbursement considerations for molecular diagnostics.

All qualified applicants will receive consideration for employment without regard to race, national origin, religion, age, color, sex, sexual orientation, gender identity, disability, or protected veteran status.
Pay Range (will vary based on location & experience) $151,000.00 - $175,000.00 Annually, Plus Bonus
In all instances, the salary paid will satisfy minimum salary laws.

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