Machine Learning Data Scientist – Research Translation & Prototyping
Contract Corp To Corp
Contract W2
12 Months
On-site
$70 - $80/hr
Talent Software Services, Inc
Fitment
Dice Job Match Score™
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Job Details
Skills
- MACHINE LEARNING ENGINEER
- MACHINE LEARNING SCIENTIST
- APPLIED SCIENTIST
- DATA SCIENTIST
- AI ENGINEER
- RESEARCH ENGINEER
- RESEARCH SCIENTIST
- PYTHON
- MACHINE LEARNING
- DEEP LEARNING
- GENERATIVE AI
- LLM
- LARGE LANGUAGE MODEL
- FOUNDATION MODEL
- TRANSFORMER
- RETRIEVAL AUGMENTED GENERATION
- RAG
- AGENTIC AI
- AI AGENT*
- MULTIMODAL
- PYTORCH
- TENSORFLOW
- JAX
- HUGGING FACE
- PROTOTYPE
- PROOF OF CONCEPT
Summary
Typical Day in the Role
• Purpose of the Team: The team supports research initiatives by rapidly applying, augmenting, and developing AI/ML capabilities across various projects.
• Key projects: This role will contribute to ___________.
• Project Gecko (language models for underrepresented African languages on AI training sets)
• Aurora (weather prediction model adapted for energy applications)
• Emerging work in policy-driven and memory-based architectures
Job Description:
Machine Learning Data Scientist – Research Translation & Prototyping
Summary:
As a Machine Learning Data Scientist, you will collaborate closely with researchers, engineers, designers, and product partners to evaluate emerging AI technologies, build rapid prototypes, and develop Client machine learning solutions that make advanced research understandable, usable, and testable. You will design experiments, create evaluation frameworks, fine-tune and validate models, and help identify which technologies warrant broader investment and adoption.
This role is ideal for a technically strong builder who enjoys ambiguity, learns quickly, and can move fluidly between research papers, datasets, prototypes, and production-scale systems. Success requires scientific rigor, strong product judgment, and a passion for turning breakthrough ideas into tools, workflows, and experiences that empower researchers, developers, and customers.
This role is ideal for a technically strong builder who enjoys ambiguity, learns quickly, and can move fluidly between research papers, datasets, prototypes, and production-scale systems. Success requires scientific rigor, strong product judgment, and a passion for turning breakthrough ideas into tools, workflows, and experiences that empower researchers, developers, and customers.
Candidates should be prepared to discuss projects that demonstrate the ability to translate research, emerging technology, or Client ideas into working prototypes, experiments, or deployed solutions.
Job Responsibilities:
• Fine-tune and improve a variety of sophisticated software implementation projects
• Gather and analyze system requirements, document specifications, and develop software solutions to meet client needs and data
• Analyze and review enhancement requests and specifications
• Implement system software and customize to client requirements
• Prepare the detailed software specifications and test plans
• Code new programs to client''s specifications and create test data for testing
• Modify existing programs to new standards and conduct unit testing of developed programs
• Create migration packages for system testing, user testing, and implementation
• Provide quality assurance reviews
• Perform post-implementation validation of software and resolve any bugs found during testing
Additional Responsibilities:
• Collaborate with companies Research teams to evaluate, adapt, and operationalize emerging AI and machine learning innovations into functional prototypes and experimental systems.
• Design and execute quantitative and qualitative experiments that measure model performance, user engagement, research impact, and technology adoption.
• Develop evaluation frameworks, benchmarks, and success metrics for foundation models, generative AI systems, multimodal experiences, and agent-based workflows.
• Fine-tune, validate, and benchmark machine learning models using real-world datasets and emerging research techniques.
• Build rapid prototypes and proof-of-concepts that help researchers, partners, and stakeholders assess the practical value of new technologies.
• Stay current with advances in machine learning, generative AI, agentic systems, multimodal models, and evaluation methodologies, identifying opportunities to apply new capabilities across companies Research.
Qualifications:
• Bachelor''s degree in a technical field such as computer science, computer engineering or related field required
• 5-7 years experience required
• Strong technical foundations in software engineering, machine learning, statistics, and experimental design.
•Experience building data-intensive applications, machine learning systems, experimentation platforms, or AI-powered products.
• Experience evaluating, debugging, and improving machine learning models, data pipelines, and AI-powered applications.
• Experience in programming and experience with problem diagnosis and resolution
• Ability to thrive in ambiguous, rapidly changing environments where requirements evolve through experimentation and discovery.
•Experience with foundation models, generative AI systems, multimodal models, agentic workflows, retrieval-augmented generation (RAG), or related AI technologies.
Explain a typical day in the role.:
No two days look exactly alike. One week you might be evaluating a new foundation model, the next building a prototype with researchers, and the following week presenting findings that influence product, research, or investment decisions.
What is the ideal background of a candidate for this role?:
The ideal candidate has experience in machine learning, data science, or applied AI, with a demonstrated ability to translate emerging research into practical prototypes, experiments, and insights. They should be comfortable working in ambiguous, fast-moving environments, designing evaluations, analyzing data, collaborating across disciplines, and communicating technical findings to diverse audiences. Experience with foundation models, generative AI, research-driven development, and rapid prototyping is highly desirable.
What are unique selling points that would get candidates interested in your role over another?:
This role sits at the intersection of companies Research and applied AI innovation. Candidates will work directly with cutting-edge research, helping transform breakthrough ideas into prototypes, experiments, and technologies that influence future companies products and experiences. The position offers unusual breadth, allowing individuals to work across multiple AI domains, collaborate with leading researchers, contribute to publications and patents, and operate in a small, highly autonomous team where creativity, experimentation, and technical excellence are equally valued.
How will contractor performance be measured?:
Performance will be measured through successful delivery of prototypes, experiments, and AI/ML solutions; the quality of technical contributions; the ability to generate actionable insights through data and experimentation; collaboration with cross-functional teams; and the overall impact of the work on research validation, technology adoption, and strategic decision-making.
• Best vs. Average: The ideal resume would contain ____________.
→ Demonstrates strong flexibility
→ Ability to rapidly ramp on new projects (1–3 days), and deliver results quickly (within ~5 days)
→ Has hands-on experience with AI-assisted coding and rapid prototyping
→ Bachelor''s degree in a technical field such as computer science, computer engineering or related field required
Top 3 Must-Have HARD Skills & years of experience for each:
1. Machine Learning & Applied AI Development (5-7 years)
2. Data Science, Experimentation & Model Evaluation (5-7 years)
3. Software Engineering & Rapid Prototyping (5-7 years)
• Purpose of the Team: The team supports research initiatives by rapidly applying, augmenting, and developing AI/ML capabilities across various projects.
• Key projects: This role will contribute to ___________.
• Project Gecko (language models for underrepresented African languages on AI training sets)
• Aurora (weather prediction model adapted for energy applications)
• Emerging work in policy-driven and memory-based architectures
Job Description:
Machine Learning Data Scientist – Research Translation & Prototyping
Summary:
As a Machine Learning Data Scientist, you will collaborate closely with researchers, engineers, designers, and product partners to evaluate emerging AI technologies, build rapid prototypes, and develop Client machine learning solutions that make advanced research understandable, usable, and testable. You will design experiments, create evaluation frameworks, fine-tune and validate models, and help identify which technologies warrant broader investment and adoption.
This role is ideal for a technically strong builder who enjoys ambiguity, learns quickly, and can move fluidly between research papers, datasets, prototypes, and production-scale systems. Success requires scientific rigor, strong product judgment, and a passion for turning breakthrough ideas into tools, workflows, and experiences that empower researchers, developers, and customers.
This role is ideal for a technically strong builder who enjoys ambiguity, learns quickly, and can move fluidly between research papers, datasets, prototypes, and production-scale systems. Success requires scientific rigor, strong product judgment, and a passion for turning breakthrough ideas into tools, workflows, and experiences that empower researchers, developers, and customers.
Candidates should be prepared to discuss projects that demonstrate the ability to translate research, emerging technology, or Client ideas into working prototypes, experiments, or deployed solutions.
Job Responsibilities:
• Fine-tune and improve a variety of sophisticated software implementation projects
• Gather and analyze system requirements, document specifications, and develop software solutions to meet client needs and data
• Analyze and review enhancement requests and specifications
• Implement system software and customize to client requirements
• Prepare the detailed software specifications and test plans
• Code new programs to client''s specifications and create test data for testing
• Modify existing programs to new standards and conduct unit testing of developed programs
• Create migration packages for system testing, user testing, and implementation
• Provide quality assurance reviews
• Perform post-implementation validation of software and resolve any bugs found during testing
Additional Responsibilities:
• Collaborate with companies Research teams to evaluate, adapt, and operationalize emerging AI and machine learning innovations into functional prototypes and experimental systems.
• Design and execute quantitative and qualitative experiments that measure model performance, user engagement, research impact, and technology adoption.
• Develop evaluation frameworks, benchmarks, and success metrics for foundation models, generative AI systems, multimodal experiences, and agent-based workflows.
• Fine-tune, validate, and benchmark machine learning models using real-world datasets and emerging research techniques.
• Build rapid prototypes and proof-of-concepts that help researchers, partners, and stakeholders assess the practical value of new technologies.
• Stay current with advances in machine learning, generative AI, agentic systems, multimodal models, and evaluation methodologies, identifying opportunities to apply new capabilities across companies Research.
Qualifications:
• Bachelor''s degree in a technical field such as computer science, computer engineering or related field required
• 5-7 years experience required
• Strong technical foundations in software engineering, machine learning, statistics, and experimental design.
•Experience building data-intensive applications, machine learning systems, experimentation platforms, or AI-powered products.
• Experience evaluating, debugging, and improving machine learning models, data pipelines, and AI-powered applications.
• Experience in programming and experience with problem diagnosis and resolution
• Ability to thrive in ambiguous, rapidly changing environments where requirements evolve through experimentation and discovery.
•Experience with foundation models, generative AI systems, multimodal models, agentic workflows, retrieval-augmented generation (RAG), or related AI technologies.
Explain a typical day in the role.:
No two days look exactly alike. One week you might be evaluating a new foundation model, the next building a prototype with researchers, and the following week presenting findings that influence product, research, or investment decisions.
What is the ideal background of a candidate for this role?:
The ideal candidate has experience in machine learning, data science, or applied AI, with a demonstrated ability to translate emerging research into practical prototypes, experiments, and insights. They should be comfortable working in ambiguous, fast-moving environments, designing evaluations, analyzing data, collaborating across disciplines, and communicating technical findings to diverse audiences. Experience with foundation models, generative AI, research-driven development, and rapid prototyping is highly desirable.
What are unique selling points that would get candidates interested in your role over another?:
This role sits at the intersection of companies Research and applied AI innovation. Candidates will work directly with cutting-edge research, helping transform breakthrough ideas into prototypes, experiments, and technologies that influence future companies products and experiences. The position offers unusual breadth, allowing individuals to work across multiple AI domains, collaborate with leading researchers, contribute to publications and patents, and operate in a small, highly autonomous team where creativity, experimentation, and technical excellence are equally valued.
How will contractor performance be measured?:
Performance will be measured through successful delivery of prototypes, experiments, and AI/ML solutions; the quality of technical contributions; the ability to generate actionable insights through data and experimentation; collaboration with cross-functional teams; and the overall impact of the work on research validation, technology adoption, and strategic decision-making.
• Best vs. Average: The ideal resume would contain ____________.
→ Demonstrates strong flexibility
→ Ability to rapidly ramp on new projects (1–3 days), and deliver results quickly (within ~5 days)
→ Has hands-on experience with AI-assisted coding and rapid prototyping
→ Bachelor''s degree in a technical field such as computer science, computer engineering or related field required
Top 3 Must-Have HARD Skills & years of experience for each:
1. Machine Learning & Applied AI Development (5-7 years)
2. Data Science, Experimentation & Model Evaluation (5-7 years)
3. Software Engineering & Rapid Prototyping (5-7 years)
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
- Dice Id: talmn001
- Position Id: 26-07348
- Posted 1 day ago
Company Info
We pride ourselves in making sure that diversity in the workplace is at the forefront of our business. Our Founder, Dave Iacarella, is an Army Veteran who is committed to giving back to fellow Veterans. We are proud of our history of transitioning military Veterans into the workforce with companies that value their service. TALENT helps companies meet their veteran and diversity spend initiatives and requirements. We are committed to supporting veteran and diverse organizations.
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