Machine Learning Researcher (Remote)
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Key skills for this role
About the Role
This contract role is for a Machine Learning Researcher to contribute domain expertise to train and refine AI systems. Responsibilities include leading research, designing deep learning algorithms, and collaborating with engineering teams.
Key Skills for This Role
Responsibilities
- Lead and conduct cutting edge research in machine learning and artificial intelligence domains to advance model capabilities and performance
- Design, implement, and evaluate state of the art deep learning algorithms using frameworks such as TensorFlow and other relevant tools
- Collaborate closely with engineering teams to translate research breakthroughs into scalable, production ready solutions with measurable impact
- Publish research findings in peer reviewed venues and contribute actively to the global AI/ML scholarly community through conferences and open source efforts
- Continuously monitor and integrate advancements from the research community to maintain the team at the forefront of technological innovation
- Document methodologies, experiments, results, and insights clearly for both technical and non technical stakeholders to support knowledge sharing and decision making
Requirements
- Domain expertise in a relevant field such as finance, healthcare, engineering, or other specialized domains, enabling high quality contributions to AI training and evaluation
- Hands on experience with deep learning frameworks including TensorFlow, PyTorch, or equivalent, with proven ability to implement and optimize models
- Strong research acumen demonstrated through prior publications, technical reports, or contributions to open source projects in machine learning or related areas
- Ability to design and execute experiments, analyze results using statistical and qualitative methods, and iterate toward robust, reproducible outcomes
- Clear communication skills with experience translating technical concepts for diverse audiences, including engineers, product teams, and external partners
- Familiarity with reinforcement learning environments, data annotation best practices, or human in the loop AI systems is a strong plus
Full Job Posting
Role Overview
- We are hiring for one of our clients, seeking a Machine Learning Researcher to work on a contractor basis.
- This role involves contributing domain expertise to train and refine next generation AI systems through high quality, real world input.
- The work directly shapes how models learn, reason, and perform across industries such as finance, healthcare, and engineering.
- Candidates need not have prior AI experience; domain knowledge is the primary value delivered.
Key Responsibilities
- Lead and conduct cutting edge research in machine learning and artificial intelligence domains to advance model capabilities and performance.
- Design, implement, and evaluate state of the art deep learning algorithms using frameworks such as TensorFlow and other relevant tools.
- Collaborate closely with engineering teams to translate research breakthroughs into scalable, production ready solutions with measurable impact.
- Publish research findings in peer reviewed venues and contribute actively to the global AI/ML scholarly community through conferences and open source efforts.
- Continuously monitor and integrate advancements from the research community to maintain the team at the forefront of technological innovation.
- Document methodologies, experiments, results, and insights clearly for both technical and non technical stakeholders to support knowledge sharing and decision making.
Required Skills & Qualifications
- Domain expertise in a relevant field such as finance, healthcare, engineering, or other specialized domains, enabling high quality contributions to AI training and evaluation.
- Hands on experience with deep learning frameworks including TensorFlow, PyTorch, or equivalent, with proven ability to implement and optimize models.
- Strong research acumen demonstrated through prior publications, technical reports, or contributions to open source projects in machine learning or related areas.
- Ability to design and execute experiments, analyze results using statistical and qualitative methods, and iterate toward robust, reproducible outcomes.
- Clear communication skills with experience translating technical concepts for diverse audiences, including engineers, product teams, and external partners.
- Familiarity with reinforcement learning environments, data annotation best practices, or human in the loop AI systems is a strong plus.
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