Applied Machine Learning Engineer
Vulcan Elements · Research Triangle Park, NC
Posted about 3 months ago
or apply directly on Vulcan Elements's site. We never take the application ourselves.
Is this posting real?
- This role has been open
- 80 days Vulcan Elements's roles stay open a median of 80 days
- Reposted
- No
- Salary listed
- No 0% of Vulcan Elements's roles list one
- Ghost-job risk at Vulcan Elements
- high 48 stale, 2 reposted of 49 open
- Hiring momentum
- 66 roles opened in the last 90 days ↑ up vs. the prior 90 days
- Last confirmed on the employer's board
- 2026-10-22
Measured from postings appearing on and disappearing from Vulcan Elements's own greenhouse board since 2026-08-03. Full hiring picture for Vulcan Elements.
About this role
As an Applied Machine Learning Engineer at Vulcan Elements, you will focus on developing machine learning solutions to enhance manufacturing processes and business operations. Your role involves identifying operational problems, preparing data, developing models, and integrating these solutions into existing workflows. Collaboration with various teams is essential to translate technical requirements and ensure that the developed tools meet operational needs.
- benefits
- 1/5
- freshness
- 1/5
- career value
- 4/5
- role clarity
- 5/5
- pay transparency
- 0/5
Scored from the posting itself — how clearly the role is described, how much it says about pay and benefits, and how recently it was listed. Not a judgement of Vulcan Elements as an employer.
What you need
- 5+ years of experience in machine learning, applied data science, software engineering, data engineering, or a closely related technical role, with a track record of building and deploying production systems
- Strong proficiency in Python and SQL, including experience writing maintainable production code
- Demonstrated ability to carry an ambiguous business or operational problem through data preparation, solution design, implementation, and deployment
- Experience building APIs, data products, or decision-support tools that are used by non-technical stakeholders
- Strong grounding in statistics, model evaluation, experimental design, and common supervised and unsupervised machine learning methods
- Experience working with incomplete, inconsistent, or operational data and making sound decisions despite imperfect information
Nice to have
- Experience in a manufacturing, industrial, laboratory, or operations-heavy environment
- Familiarity with manufacturing concepts such as genealogy, recipes, work orders, process parameters, yield, scrap, quality holds, equipment states, and process capability
- Experience working with time-series, sensor, image, document, or other forms of manufacturing and laboratory data
- Experience deploying and monitoring machine learning models, including familiarity with experiment tracking, model versioning, and model-performance monitoring
- Experience with optimization, simulation, anomaly detection, computer vision, natural-language processing, or large language model applications
Worth weighing
- The role requires strong collaboration across various teams, which may involve navigating different levels of technical understanding.
- No specific salary or benefits information is provided in the posting, which may be a consideration for candidates.
- The job involves working with operational data, which can be incomplete or inconsistent, requiring strong problem-solving skills.
Summarised from Vulcan Elements's posting. Read the full original.
Listed by Vulcan Elements on their greenhouse job board, last confirmed open on 2026-10-22. PitchMeAI is not the employer.
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