Machine Learning Data Scientist – Research Translation & Prototyping
New
O
Only External PostingsTechnology Solutions
RemoteFull-TimeSenior
Salary145,000 - 155,000 USD per year
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Job Details
- Experience
- 5–7+ years
- Required Skills
- Machine LearningData sciencePrototypingSoftware EngineeringGenerative AI
Requirements
- Bachelor's degree in Computer Science, Computer Engineering, Data Science, Mathematics, Statistics, or a related technical field.
- 5–7+ years of professional experience in machine learning, data science, applied AI, software engineering, or a related discipline.
- Strong experience developing machine learning models and AI-powered solutions.
- Demonstrated experience with data science methodologies, experimentation, model evaluation, and statistical analysis.
- Hands-on software engineering experience, including coding, debugging, testing, and deployment.
- Experience building data-intensive applications, machine learning systems, experimentation platforms, or AI-enabled products.
- Strong programming skills and the ability to diagnose and resolve technical issues.
- Experience evaluating, improving, and maintaining machine learning models, data pipelines, and AI applications.
- Ability to quickly learn new technologies, adapt to changing priorities, and contribute effectively in ambiguous, fast-moving environments.
- Strong communication skills with the ability to explain technical concepts and findings to both technical and non-technical audiences.
- Experience working collaboratively across research, engineering, product, and business teams.
Responsibilities
- Collaborate with research, engineering, and cross-functional teams to evaluate emerging AI and machine learning technologies and determine their practical value.
- Design, develop, and implement machine learning models, AI-powered applications, and experimental systems.
- Build rapid prototypes and proof-of-concept solutions to validate new technologies and research concepts.
- Fine-tune, benchmark, validate, and improve machine learning models using real-world datasets.
- Develop evaluation frameworks, benchmarks, and success metrics for AI systems, foundation models, generative AI solutions, multimodal experiences, and agent-based workflows.
- Design and execute quantitative and qualitative experiments to assess model performance, user engagement, technology adoption, and overall effectiveness.
- Analyze system requirements, document technical specifications, and develop software solutions aligned with project objectives.
- Develop, test, and maintain software applications and supporting infrastructure.
- Support deployment, validation, and post-implementation monitoring of solutions.
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