Applied Machine Learning Scientist

🔥 0 minutes ago

🇺🇸 United States – Remote

💵 $105k - $185k / year

⏰ Full Time

🟢 Junior

🟡 Mid-level

🤖 Machine Learning Engineer

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 Ghost score 0%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

Apply Now

Find Similar Remote Jobs

Set Up Email Alert For New Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

Workiva

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2008

💼 Consulting

🏥 Healthcare

📦 Logistics

Consulting • Healthcare • Logistics

Workiva is a cloud-based, AI-powered platform that unifies financial reporting, risk and compliance management, and sustainability reporting. It enables teams to connect data across systems, collaborate in real time, automate reporting (including XBRL tagging), and maintain auditability and traceability for regulated disclosures and assurance processes. Workiva serves large enterprises and finance, legal, audit, and sustainability teams to accelerate reporting, improve accuracy, and reduce risk.

📋 Description

• Contribute to the development, testing, and deployment of AI and ML solutions • Build, evaluate, and iterate on machine learning models, experiments, prototypes, and data-driven features • Assist with data preparation, feature development, model training, model evaluation, error analysis, and experiment documentation • Write clean, efficient, testable, and maintainable code for ML and AI applications • Partner with applied scientists, engineers, product managers, and stakeholders to translate requirements into technical tasks • Participate in experimentation and measurement, including defining hypotheses, selecting evaluation metrics, and interpreting results • Develop and maintain reusable tools, libraries, datasets, and workflows supporting the ML development lifecycle • Support integration of models and AI capabilities into scalable product and platform solutions • Learn and apply MLOps, cloud, observability, testing, and operational practices • Assist with monitoring and improving ML systems for quality, performance, reliability, and efficiency • Document technical approaches, experiment results, model limitations, and implementation decisions • Participate in code reviews, design discussions, team planning, and knowledge-sharing activities • Stay current with machine learning, generative AI, LLMs, statistical modeling, and applied AI techniques • Contribute ideas improving experimentation culture, engineering practices, and product outcomes

🎯 Requirements

• Bachelor’s degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative field; equivalent practical experience may be considered • 0–2 years of hands-on experience through professional work, internships, research, coursework, or projects in machine learning, AI, data science, software engineering, or a related technical area • Proficiency in Python, R, or a similar language for data analysis, model development, or software development • Foundational knowledge of machine learning, including data preparation, feature engineering, training, validation, model evaluation, and common performance metrics • Familiarity with ML and data-science tools such as PyTorch, TensorFlow, Scikit-learn, Hugging Face, pandas, NumPy, SciPy, or Statsmodels • Exposure to generative AI, including prompt engineering, retrieval-augmented generation, embeddings, LLM evaluation, fine-tuning, or agentic workflows • Familiarity with SQL, APIs, data pipelines, model-serving concepts, cloud platforms, or MLOps practices • Exposure to software-engineering practices such as Git, code review, testing, CI/CD, or containers • Strong analytical, communication, and collaboration skills, with curiosity and a willingness to learn in a fast-moving applied AI environment • Interest in building responsible, reliable, and measurable AI solutions that address customer needs • Minimal travel required, up to 10% • Reliable internet access is required for any period of time working remotely and not in a Workiva office • Candidates must be authorized to work in the U.S. on a permanent basis

🏖️ Benefits

• A discretionary bonus typically paid annually • Restricted Stock Units granted at time of hire • 401(k) match • Comprehensive employee benefits package • Flexible work location: office or remotely from any location within the country of employment • Reasonable accommodations for applicants with disabilities