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machine engineer

MORSE Corp

<div>
 
 MORSE Corp is an employee owned, small business based in Cambridge, MA, Arlington, VA, and Seattle, WA with a history of fielding
 
 cutting-edge
 
 
 technology. MORSE boasts a specially selected team of scientists, engineers, and software developers to deliver best-in-class technical solutions that solve difficult multidisciplinary problems faced by the US National Security Ecosystem.
 
 
 &nbsp;
 
 
 
 
 We are seeking a Machine Learning Engineer to join our team at MORSE.  You will play a pivotal role in designing, implementing, and managing complex ML algorithms and systems, with a focus on computer vision (CV) and other types of data. You will be responsible for acquiring truth data, integrating algorithms, testing algorithms, combining algorithms, reviewing literature to stay on top of the latest-and-greatest methods, analyzing data from field tests, and developing advanced algorithms.  MORSE&rsquo;s AI &amp; ML work crosses modalities, and experience or interest in the fields of Large Language Models (LLM), audio analysis, computer vision, and advanced reasoning is a plus. You will work with MORSE&rsquo;s current team of engineers to transition algorithms to production, which may run on on-prem servers, on the cloud, or on a real-time embedded system. You will be part of our team working to accelerate our US National Security customers abilities to use natural language processing capabilities in mission-critical environments.
 
 
 &nbsp;
 
 
 
 Responsibilities:
 
 
 &nbsp;
 
 <ul>
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 Develop, fine-tune, train, and optimize Computer Vision algorithms processing tasks such as object detection and tracking.&nbsp;
 
 
 &nbsp;
 
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 Use MLOps tools for efficient experiment tracking, data management, and reproducibility
 
 
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 Write robust, efficient, and maintainable code
 
 
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 Track the latest advancements with machine learning research to bring new techniques and methodologies to MORSE
 
 
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 Conduct experiments and perform rigorous evaluations to assess the effectiveness and efficiency of CV models
 
 
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 Skills and Requirements:
 
 
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 US CITIZENSHIP REQUIRED and the ability to obtain a U.S. Security Clearance
 
 
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 </ul>
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 Masters or Ph.D. in Computer Science, Computer Engineering, Data Science, Aerospace, Mathematics, Physics, or related field
 
 
 &nbsp;
 
 </li>
 </ul>
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 <li>
 
 Proven experience in applying CV models, techniques, frameworks, and libraries to implement and fine-tune models
 
 
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 </ul>
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 Proven experience testing and validating the performance of AI technologies in real-world applications
 
 
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 Proficiency in Python
 
 
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 </ul>
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 Experience with cloud platforms (AWS and Azure)
 
 
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 Experience with Docker
 
 
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 Experience with MLOps tools such as Airflow, MLFlow, AimStack, etc.
 
 
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 Exceptional communication skills and the ability to work well with customers
 
 
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 Understanding of Department of Defense requirements and standards is a plus
 
 
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 &nbsp;
 
 
 
 
 
 
 &nbsp;
 
 
 
 
 &nbsp;
 
 
 
 MORSE Corp&rsquo;s salary range for this role carefully considers a wide range of compensation factors, including but not limited to, prior experience, education, skills and expertise, location, internal equity, and other factors that are job related and consistent with business need. Therefore, final offer amounts may vary from the amount stated. Depending on role eligibility, total compensation may also include bonus, stock, 401(k) match, paid time off, medical, dental, vision and life insurance.Employees also receive 10 paid holidays per year. MORSE maintains an &ldquo;open&rdquo; leave policy that does not restrict exempt, regular full-time employees to a specific&nbsp;number of paid sick or vacation days. However, this policy is not an &ldquo;unlimited&rdquo; paid leave policy.&nbsp;
 
 
 Compensation: $90,000 USD - $210,000 USD
 
 
 The team at MORSE takes pride in being the smart team that is easy to work with. We focus on steady, long-term success while maintaining a collaborative, enjoyable work experience for our employees. Our team values work-life balance through flexibility and other programs, along with a comprehensive benefits package for employees and families. For more information, please visit www.morsecorp.com.
 
 
 
 &nbsp;
 
 
</div>

Machine Learning Engineer

PitchBook

<div>
 At PitchBook, a Morningstar company, we are always looking forward. We continue to innovate, evolve, and invest in ourselves to bring out the best in everyone. We&rsquo;re deeply collaborative and thrive on the excitement, energy, and fun that reverberates throughout the company.
 
 
 Our extensive learning programs and mentorship opportunities help us create a culture of curiosity that pushes us to always find new solutions and better ways of doing things. The combination of a rapidly evolving industry and our high ambitions means there&rsquo;s going to be some ambiguity along the way, but we excel when we challenge ourselves. We&rsquo;re willing to take risks, fail fast, and do it all over again in the pursuit of excellence.
 
 
 If you have a good attitude and are willing to roll up your sleeves to get things done, PitchBook is the place for you.
 
 
 
 About The Role
 
 
 
 As a member of the Product and Engineering team at PitchBook, you will be part of a team of big thinkers, innovators, and problem solvers who strive to deepen the positive impact we have on our customers and our company every day. We value curiosity and the drive to find better ways of doing things. We thrive on customer empathy, which remains our focus when creating excellent customer experiences through product innovation.
 
 
 We know that greatness is achieved through collaboration and diverse points of view, so we work closely with partners around the globe. As a team, we assume positive intent in each other&rsquo;s words and actions, value constructive discussions, and foster a respectful working environment built on integrity, growth, and business value. We invest heavily in our people, who are eager to learn and constantly improve. Join our team and grow with us!
 
 
 As a Machine Learning Engineer (MLE) on the AI &amp; ML (Insights) team, you will play a critical role in delivering AI-powered features that extract meaningful insights from PitchBook&rsquo;s wealth of structured and unstructured data including reports, news, and other textual content. This role requires deep technical expertise in advanced data analytics and machine learning, as well as a hands-on approach to designing, building, and optimizing ML solutions that power user-facing features on the PitchBook Platform.
 
 
 You will be deeply involved in the end-to-end development and operationalization of ML models, including their architecture, training, deployment, and ongoing maintenance. Your focus will span across natural language processing (NLP), generative AI (GenAI), large language models (LLMs), and scalable data systems. You will be expected to tackle complex technical challenges, contribute to architectural decisions, and collaborate closely with other engineers, data scientists, and product managers to ensure that your work aligns with business goals and AI/ML strategy.
 
 
 Your contributions will help unlock unique value for PitchBook customers by improving the speed, discoverability, quality, and quantity of insights available on the platform. This includes developing models that can infer meaning and structure from millions of discrete data sources and applying ML to enrich our datasets with predictive and generative intelligence.
 
 
 
 Primary Job Responsibilities
 
 
 
 <ul>
 <li>
 Deliver high-impact AI and ML capabilities that drive insight generation on the PitchBook Platform. Ensure your work contributes to broader business goals and is aligned with the team's strategic priorities
 </li>
 <li>
 Provide hands-on expertise in designing, building, and deploying AI/ML models and services with a focus on NLP, summarization, semantic search, classification, and prediction. Contribute to the development of scalable, high-performance systems that meet production-grade reliability and efficiency standards
 </li>
 <li>
 Contribute to a culture of technical excellence by sharing knowledge, pairing with teammates, and actively participating in code and design reviews. Provide situational guidance to junior engineers and contribute to team best practices
 </li>
 <li>
 Build and optimize models that leverage classifiers, transformers, LLMs, and other NLP techniques to generate meaningful insights from structured and unstructured data. Integrate these models into the broader AI/ML infrastructure in collaboration with partner teams
 </li>
 <li>
 Collaborate with engineering, product management, and data collection teams to ensure models are informed by high-quality data and support strategic product goals
 </li>
 <li>
 Explore and experiment with emerging technologies, methodologies, and tools in the fields of GenAI, NLP, and search. Translate research findings into practical solutions that enhance PitchBook&rsquo;s AI capabilities
 </li>
 <li>
 Contribute to best practices in model transparency, monitoring, evaluation, and compliance. Help maintain high standards of security, data integrity, and responsible AI use across your projects
 </li>
 <li>
 Participate in the technical evaluation of candidates and help onboard new team members by contributing to documentation, pairing, and knowledge-sharing practices
 </li>
 <li>
 Apply principles from Agile, Lean, and Fast-Flow methodologies to support efficient model development and deployment cycles
 </li>
 <li>
 Support the vision and values of the company through role modeling and encouraging desired behaviors
 </li>
 <li>
 Participate in various company initiatives and projects as requested
 
 
 </li>
 </ul>
 
 Skills And Qualifications
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in Computer Science, Mathematics, Data Science, or related technical field, advanced degrees are preferred
 </li>
 <li>
 2+ years of experience in software engineering or machine learning engineering, with a strong focus on AI/ML applications in insight generation, summarization, semantic search, and prediction
 </li>
 <li>
 Demonstrated expertise in natural language processing (NLP) and machine learning, including hands-on experience with classifiers, transformer models, large language models (LLMs), and widely used ML and data science libraries such as scikit-learn, pandas, numpy, TensorFlow, and PyTorch
 </li>
 <li>
 Experience delivering production-grade GenAI or LLM-based systems with measurable business impact
 </li>
 <li>
 Familiarity with the LangChain ecosystem, including tools such as LangSmith and LangGraph, and experience using them in production environments is a strong plus
 </li>
 <li>
 Proficiency in building and maintaining scalable data pipelines and distributed systems using technologies such as Apache Kafka, Airflow, and cloud data platforms like Snowflake
 </li>
 <li>
 Strong programming skills in Python and SQL, with working knowledge of additional languages such as Java or Scala considered a plus
 </li>
 <li>
 Practical experience with cloud-native development, containerization, and orchestration technologies such as Docker and Kubernetes
 </li>
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 Demonstrated ability to solve complex technical problems, contribute to architectural decisions, and deliver high-performance, reliable solutions
 </li>
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 Excellent communication and collaboration skills, with experience working cross-functionally with product managers, engineers, and data scientists in globally distributed teams
 </li>
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 Experience working in fast-paced, data-driven environments. Prior exposure to fintech or financial data platforms is a strong advantage
 </li>
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 Experience authoring research papers for peer-reviewed AI/ML conferences (e.g., NeurIPS, ICML, ACL) and participating in the broader AI research community is strongly preferred
 </li>
 <li>
 Must be authorized to work in the United States without the need for visa sponsorship now or in the future
 
 
 </li>
 </ul>
 
 Benefits + Compensation at PitchBook:
 
 
 
 Physical Health
 
 
 <ul>
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 Comprehensive health benefits
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 Additional medical wellness incentives
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 STD, LTD, AD&amp;D, and life insurance
 
 
 </li>
 </ul>
 Emotional Health
 
 
 <ul>
 <li>
 Paid sabbatical program after four years
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 Paid family and paternity leave
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 Annual educational stipend
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 Ability to apply for tuition reimbursement
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 CFA exam stipend
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 Robust training programs on industry and soft skills
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 Employee assistance program
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 Generous allotment of vacation days, sick days, and volunteer days
 
 
 </li>
 </ul>
 Social Health
 
 
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 Matching gifts program
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 Employee resource groups
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 Subsidized emergency childcare
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 Dependent Care FSA
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 Company-wide events
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 Employee referral bonus program
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 Quarterly team building events
 
 
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 </ul>
 Financial Health
 
 
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 401k match
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 Shared ownership employee stock program
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 Monthly transportation stipend
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 Please be aware the above PitchBook benefit and perk offerings are subject to corresponding plan and policy documents and may change during the course of your employment.
 
 
 </li>
 </ul>
 
 Compensation
 
 
 
 <ul>
 <li>
 Annual base salary: $125,000-$180,000
 </li>
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 Target annual bonus percentage: 10%
 
 
 </li>
 </ul>
 
 Working Conditions
 
 
 
 At the heart of our company is a belief in the power of in-person collaboration. Being together in the office fuels our creativity, strengthens our connections, and drives the innovation that sets us apart. Our culture is built on spontaneous moments&mdash;those hallway conversations, whiteboard brainstorms, and shared celebrations in each of our global offices&mdash;that simply can&rsquo;t be replicated remotely. This role is expected to be in the office 5 days a week.
 
 
 The job conditions for this position are in a standard office setting. Employees in this position use PC and phone on an on-going basis throughout the day. Limited corporate travel may be required to remote offices or other business meetings and events.
 
 
 We are excited to get to know you and your background. Concerned that you might not meet every requirement? We encourage you to still apply as you might be the right candidate for the role or other roles at PitchBook.
 
 
</div>

Scowtt

<div>
 
 About Scowtt
 
 
 
 Scowtt is an early-stage startup transforming the way businesses convert leads into customers through AI/ML marketing optimization and fully autonomous sales experiences. By integrating CRM, web signals, and product interaction data into a real-time conversion model, we help businesses turn interest into action&mdash;immediately. We&rsquo;re growing fast, and onboarding new customers quickly and cleanly is core to our success.
 
 
 
 About The Role
 
 
 
 We are looking for a motivated, entry-level Machine Learning Engineer to help build, train, and deploy ML models that power our Marketing AI and AI Sales Agent products. This role is ideal for new graduates or early-career engineers who want hands-on experience working on real ML systems in a fast-paced, collaborative startup environment.
 
 
 
 What You&rsquo;ll Do
 
 
 
 <ul>
 <li>
 Assist in training, evaluating, and deploying ML models
 </li>
 <li>
 Work with structured and behavioral data used in marketing and sales systems
 </li>
 <li>
 Help automate and maintain data and ML pipelines
 </li>
 <li>
 Collaborate with engineers to integrate ML models into AI agents
 </li>
 <li>
 Debug, optimize, and improve model and pipeline performance
 </li>
 <li>
 Learn how ML systems operate in real production environments (cloud, monitoring, iteration)
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 
 Must Have
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in Computer Science, ML, Data Science, or equivalent
 </li>
 <li>
 1-3 years of experience in data structures, algorithms
 </li>
 <li>
 1-3 years of experience with machine learning concepts and workflows
 </li>
 <li>
 1-3 years of experience in coding using Python with demonstrated strong coding skills
 
 
 </li>
 </ul>
 
 Should Have
 
 
 
 <ul>
 <li>
 Exposure to ML frameworks through coursework, projects, or internships
 </li>
 <li>
 Curiosity, ownership mindset, and eagerness to learn
 
 
 </li>
 </ul>
 
 Nice to Have
 
 
 
 <ul>
 <li>
 Hands-on project or internship experience with real datasets
 </li>
 <li>
 Exposure to cloud platforms (GCP or AWS)
 </li>
 <li>
 Familiarity with tools like BigQuery, notebooks, or basic data pipelines
 
 
 </li>
 </ul>
 
 What Success Looks Like
 
 
 
 <ul>
 <li>
 You contribute to shipping ML models with guidance
 </li>
 <li>
 You learn to debug data and model issues
 </li>
 <li>
 You steadily increase independence and ownership
 </li>
 <li>
 You build strong foundations in applied ML engineering
 
 
 </li>
 </ul>
 
 Pay Range And Compensation Package
 
 
 
 Based on the level hired at, the cash compensation for this role ranges between $100,000 to $150,000. Selected candidate/s will be eligible for standard benefits and startup equity.
 
 
 
 Equal Opportunity &amp; E-Verify Employer
 
 
 
 Scowtt is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or veteran status. We are committed to providing a workplace free of discrimination and harassment.
 
 
 This employer participates in E-Verify and will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S. For more information, please visit www.e-verify.gov.
</div>

Machine Learning Engineer I

Apple

Imagine what you can do here. Apple is a place where extraordinary people gather to do their lives best work. Together we create products and experiences people once couldn&rsquo;t have imagined, and now, can&rsquo;t imagine living without. It&rsquo;s the diversity of those people and their ideas that inspires the innovation that runs through everything we do. 
 
Description 
 
APPLE INC has the following available in Seattle, Washington. Develop software to run innovative machine learning systems in the cloud. Implement performant ML based algorithms in a distributed system and keep up to date with best practices and new technologies. Work closely with ML engineers to ensure their algorithms can be deployed efficiently in the cloud. Build software to support batch inferences for new large language models. Analyze and improve the job success rates for batch inference jobs. Optimize efficiency of the pipeline to improve throughput for large scale inference solutions. Build a scalable and efficient system to improve utilization of high-performance GPU fleet. 40 hours/week. At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $139,500 - $210,100/yr and your base pay will depend on your skills, qualifications, experience, and location. 
 
PAY &amp; BENEFITS: Apple employees also have the opportunity to become an Apple shareholder through participation in Apple&rsquo;s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple&rsquo;s Employee Stock Purchase Plan. You&rsquo;ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits: https://www.apple.com/careers/us/benefits.html. 
 
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program. 
 
Preferred Qualifications 
 
N/A 
 
Minimum Qualifications 
 
Bachelor&rsquo;s degree or foreign equivalent in Software Engineering, Computer Science, or related field and 2 years of experience in the job offered or related occupation. 
 
2 years of experience with each of the following skills is required: 
 
Applying Golang to design and develop large language model batch inference service codebase. 
 
Utilizing docker containerization and Kubernetes orchestration including AWS EKS or GCP to run batch inference service on the cloud infrastructure. 
 
Ensuring performance, scalability, security and maintainability when designing robust, large scale batch inference service. 
 
Utilizing ML Framework including PyTorch or TensorFlow to develop and optimize large language models. 
 
Applying foundation model architectures including Transformers, Encoder/Decoder to train, and fine-tune large language models. 
 
Utilizing MapReduce to develop efficient large scale data pipelines. 
 
Applying MLOps best practice to automate model deployment, monitoring, and continuous integration / continuous delivery. 
 
Utilizing hardware accelerators including GPUs or TPUs to maximize computational efficiency and reduce inference time. 
 
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant .

<div>
 
 Summary
 
 
 
 Imagine what you can do here. Apple is a place where extraordinary people gather to do their lives best work. Together we create products and experiences people once couldn&rsquo;t have imagined, and now, can&rsquo;t imagine living without. It&rsquo;s the diversity of those people and their ideas that inspires the innovation that runs through everything we do.
 
 
 
 Description
 
 
 
 APPLE INC has the following available in Seattle, Washington. Develop software to run innovative machine learning systems in the cloud. Implement performant ML based algorithms in a distributed system and keep up to date with best practices and new technologies. Work closely with ML engineers to ensure their algorithms can be deployed efficiently in the cloud. Build software to support batch inferences for new large language models. Analyze and improve the job success rates for batch inference jobs. Optimize efficiency of the pipeline to improve throughput for large scale inference solutions. Build a scalable and efficient system to improve utilization of high-performance GPU fleet. 40 hours/week. At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $139,500 - $210,100/yr and your base pay will depend on your skills, qualifications, experience, and location.
 
 
 PAY &amp; BENEFITS: Apple employees also have the opportunity to become an Apple shareholder through participation in Apple&rsquo;s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple&rsquo;s Employee Stock Purchase Plan. You&rsquo;ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses &mdash; including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits: https://www.apple.com/careers/us/benefits.html.
 
 
 Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
 
 
 
 Minimum Qualifications
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree or foreign equivalent in Software Engineering, Computer Science, or related field and 2 years of experience in the job offered or related occupation.
 </li>
 <li>
 2 years of experience with each of the following skills is required:
 </li>
 <li>
 Applying Golang to design and develop large language model batch inference service codebase.
 </li>
 <li>
 Utilizing docker containerization and Kubernetes orchestration including AWS EKS or GCP to run batch inference service on the cloud infrastructure.
 </li>
 <li>
 Ensuring performance, scalability, security and maintainability when designing robust, large scale batch inference service.
 </li>
 <li>
 Utilizing ML Framework including PyTorch or TensorFlow to develop and optimize large language models.
 </li>
 <li>
 Applying foundation model architectures including Transformers, Encoder/Decoder to train, and fine-tune large language models.
 </li>
 <li>
 Utilizing MapReduce to develop efficient large scale data pipelines.
 </li>
 <li>
 Applying MLOps best practice to automate model deployment, monitoring, and continuous integration / continuous delivery.
 </li>
 <li>
 Utilizing hardware accelerators including GPUs or TPUs to maximize computational efficiency and reduce inference time.
 
 
 </li>
 </ul>
 Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant.
 
 
 Apple accepts applications to this posting on an ongoing basis.
 
 
</div>

Docusign

<div>
 
 Company Overview
 
 
 
 Docusign brings agreements to life. Over 1.5 million customers and more than a billion people in over 180 countries use Docusign solutions to accelerate the process of doing business and simplify people&rsquo;s lives. With intelligent agreement management, Docusign unleashes business-critical data that is trapped inside of documents. Until now, these were disconnected from business systems of record, costing businesses time, money, and opportunity. Using Docusign&rsquo;s Intelligent Agreement Management platform, companies can create, commit, and manage agreements with solutions created by the #1 company in e-signature and contract lifecycle management (CLM).
 
 
 What you'll do
 
 
 Docusign is looking for a passionate, talented, and collaborative Machine Learning Engineer to join our AI Infrastructure team. Our team is responsible for building Docusign&rsquo;s centralized platform to create, manage and deploy advanced AI/ML solutions to make customer journeys throughout the Docusign Agreement Cloud more efficient. As a Machine Learning engineer, you will help support all aspects of the machine learning lifecycle, including the research platform, training and deployment pipelines, labeling and serving infrastructure. You will partner with a team of expert applied researchers who specialize in various domains, including document understanding, natural language processing (NLP), computer vision, and more to prototype and productionize solutions for real business use-cases at scale.
 
 
 This position is an individual contributor role reporting to the Senior Manager, Machine Learning.
 
 
 
 Responsibility
 
 
 
 <ul>
 <li>
 Write clean, maintainable, and well-tested code for AI infrastructure services and data pipelines under the guidance of senior engineers
 </li>
 <li>
 Assist in building and maintaining CI/CD pipelines and workflows that automate model training and deployment
 </li>
 <li>
 Help monitor the performance of deployed AI services by implementing logging, metrics, and alerting (observability) to ensure system reliability
 </li>
 <li>
 Partner with Applied Scientists and Product Managers to understand requirements and help operationalize ML models for document understanding and NLP tasks
 </li>
 <li>
 Author unit and integration tests for your code components to ensure high quality and stability of the AI platform
 </li>
 <li>
 Develop scripts and small tools to support data labeling processes and ensure data governance standards are met
 </li>
 <li>
 Learn about new ML technologies (LLMs, Triton Inference Server, Kubernetes) and engineering best practices through code reviews and mentorship actively
 
 
 </li>
 </ul>
 Job Designation
 
 
 
 Hybrid:
 
 Employee divides their time between in-office and remote work. Access to an office location is required. (Frequency: Minimum 2 days per week; may vary by team but will be weekly in-office expectation)
 
 
 Positions at Docusign are assigned a job designation of either In Office, Hybrid or Remote and are specific to the role/job. Preferred job designations are not guaranteed when changing positions within Docusign. Docusign reserves the right to change a position's job designation depending on business needs and as permitted by local law.
 
 
 What you bring
 
 
 
 Basic
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in Computer Science, or a related technical field (or equivalent experience)
 </li>
 <li>
 Experience with internships or applicable academic projects
 </li>
 <li>
 Experience with at least one major programming language, preferably Python or C#
 </li>
 <li>
 Experience with data structures, algorithms, and software engineering fundamentals
 </li>
 <li>
 Experience with version control systems (e.g., git) and writing unit tests
 </li>
 <li>
 Experience with RESTful APIs and how web services work
 
 
 </li>
 </ul>
 
 Preferred
 
 
 
 <ul>
 <li>
 Previous internship experience in software engineering, data engineering, or machine learning
 </li>
 <li>
 Coursework or academic projects related to Machine Learning, Natural Language Processing (NLP), or Computer Vision
 </li>
 <li>
 Familiarity with containerization technologies like Docker or Kubernetes
 </li>
 <li>
 Exposure to cloud platforms (AWS, Azure, or GCP)
 </li>
 <li>
 Interest in Large Language Models (LLMs) and Generative AI
 </li>
 <li>
 Experience with SQL or data processing libraries (e.g., Pandas, NumPy)
 
 
 </li>
 </ul>
 Wage Transparency
 
 
 Pay for this position is based on a number of factors including geographic location and may vary depending on job-related knowledge, skills, and experience.
 
 
 Based on applicable legislation, the below details pay ranges in the following locations:
 
 
 California: $100,300.00 - $154,900.00 base salary
 
 
 Washington, Maryland, New Jersey and New York (including NYC metro area): $94,600.00 - $137,875.00 base salary
 
 
 
 This Role Is Also Eligible For The Following
 
 
 
 <ul>
 <li>
 Bonus: Sales personnel are eligible for variable incentive pay dependent on their achievement of pre-established sales goals. Non-Sales roles are eligible for a company bonus plan, which is calculated as a percentage of eligible wages and dependent on company performance.
 </li>
 <li>
 Stock: This role is eligible to receive Restricted Stock Units (RSUs).
 
 
 </li>
 </ul>
 
 Benefits
 
 
 
 Global benefits provide options for the following:
 
 
 <ul>
 <li>
 Paid Time Off: earned time off, as well as paid company holidays based on region
 </li>
 <li>
 Paid Parental Leave: take up to six months off with your child after birth, adoption or foster care placement
 </li>
 <li>
 Full Health Benefits Plans: options for 100% employer paid and minimum employee contribution health plans from day one of employment
 </li>
 <li>
 Retirement Plans: select retirement and pension programs with potential for employer contributions
 </li>
 <li>
 Learning and Development: options for coaching, online courses and education reimbursements
 </li>
 <li>
 Compassionate Care Leave: paid time off following the loss of a loved one and other life-changing events
 
 
 </li>
 </ul>
 
 Work Authorization Notice:
 
 Please note that we do not provide visa sponsorship or immigration support for this position. Applicants must already be authorized to work in the United States on a full-time, permanent basis without the need for current or future sponsorship.
 
 
 Life at Docusign
 
 
 
 Working here
 
 
 
 Docusign is committed to building trust and making the world more agreeable for our employees, customers and the communities in which we live and work. You can count on us to listen, be honest, and try our best to do what&rsquo;s right, every day. At Docusign, everything is equal.
 
 
 We each have a responsibility to ensure every team member has an equal opportunity to succeed, to be heard, to exchange ideas openly, to build lasting relationships, and to do the work of their life. Best of all, you will be able to feel deep pride in the work you do, because your contribution helps us make the world better than we found it. And for that, you&rsquo;ll be loved by us, our customers, and the world in which we live.
 
 
 
 Accommodation
 
 
 
 Docusign is committed to providing reasonable accommodations for qualified individuals with disabilities in our job application procedures. If you need such an accommodation, or a religious accommodation, during the application process, please contact us at accommodations@docusign.com.
 
 
 If you experience any issues, concerns, or technical difficulties during the application process please get in touch with our Talent organization at taops@docusign.com for assistance.
 
 
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 This position is not eligible for employment in the following states: Alaska, Hawaii, Maine, Mississippi, North Dakota, South Dakota, Vermont, West Virginia and Wyoming.
 
 
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 It's important to us that we build a talented team that is as diverse as our customers and where all employees feel a deep sense of belonging and thrive. We encourage great talent who bring a range of perspectives to apply for our open positions. Docusign is an Equal Opportunity Employer and makes hiring decisions based on experience, skill, aptitude and a can-do approach. We will not discriminate based on race, ethnicity, color, age, sex, religion, national origin, ancestry, pregnancy, sexual orientation, gender identity, gender expression, genetic information, physical or mental disability, registered domestic partner status, caregiver status, marital status, veteran or military status, or any other legally protected category.
 
 
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</div>

Call For Referral

<div>
 
 
 Machine Learning Engineer
 
 
 
 
 Work Mode:
 
 
 Remote
 
 
 
 
 Compensation:
 
 
 $100&ndash;$120 per hour
 
 
 
 
 Work Type:
 
 
 Hourly, Independent
 
 
 
 
 Role Overview
 
 
 
 This role supports the evaluation of
 
 advanced machine learning systems
 
 in collaboration with
 
 leading AI research initiatives
 
 . It is intended for
 
 experienced machine learning engineers and researchers
 
 who can contribute to the development of
 
 high-quality evaluation suites
 
 that measure AI performance on
 
 real-world machine learning engineering tasks
 
 .
 
 
 The work focuses on translating
 
 practical ML research and engineering workflows
 
 into
 
 structured benchmarks
 
 for
 
 frontier models
 
 . This is a
 
 project-based, fully remote
 
 opportunity for professionals with
 
 strong hands-on ML research and engineering experience
 
 .
 
 
 
 Key Responsibilities
 
 
 <ul>
 <li>
 
 Design and develop
 
 detailed evaluation suites for machine learning engineering tasks
 </li>
 <li>
 
 Evaluate AI-generated solutions
 
 across model training, debugging, optimization, and experimentation workflows
 </li>
 <li>
 
 Analyze and document
 
 system behavior, performance characteristics, and limitations
 </li>
 <li>
 
 Contribute to the creation of benchmarks
 
 that reflect real-world ML engineering practices
 </li>
 <li>
 
 Maintain high standards
 
 of technical accuracy, clarity, and consistency in all deliverables
 </li>
 </ul>
 
 
 Qualifications
 
 
 <ul>
 <li>
 
 3+ years
 
 of experience in machine learning engineering or applied ML research
 </li>
 <li>
 
 Hands-on experience
 
 with model development, experimentation, and evaluation
 </li>
 <li>
 
 Background in ML research
 
 in an industry or academic setting (strongly preferred)
 </li>
 <li>
 
 Strong ability
 
 to reason about ML system design choices and technical trade-offs
 </li>
 <li>
 
 Excellent written communication skills
 
 and
 
 high attention to technical detail
 
 </li>
 </ul>
 
 
 Work &amp; Payment Details
 
 
 <ul>
 <li>
 You will operate as an
 
 independent professional
 
 </li>
 <li>
 This is a
 
 fully remote
 
 role with a
 
 flexible schedule
 
 </li>
 <li>
 Projects may be
 
 extended, shortened, or concluded
 
 based on needs and performance
 </li>
 <li>
 The work does
 
 not involve access to confidential or proprietary information
 
 from any employer, client, or institution
 </li>
 <li>
 
 Payments are made weekly
 
 via
 
 Stripe or Wise
 
 , based on services delivered
 </li>
 <li>
 Candidates requiring
 
 H1-B or STEM OPT
 
 sponsorship are
 
 not supported
 
 at this time
 </li>
 </ul>
 
 
 Application &amp; Onboarding Process
 
 
 <ul>
 <li>
 
 Upload your resume
 
 </li>
 <li>
 
 AI interview:
 
 A short
 
 15-minute
 
 conversational session to understand your background, experience, and interest in the role
 </li>
 <li>
 
 Follow-up communication
 
 within a few days with next steps and onboarding details
 </li>
 </ul>
 
 
</div>

Machine Learning Engineer (Remote)  $100 –$120/hr

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