Lead the development of machine learning solutions that improve model performance and business outcomes, owning complex modeling problems from initial investigation through production implementation.
Locations (5)
Columbus, United States
Austin, United States
Bay Area, United States
New York City, United States
Canada
Compensation
United States | Remote - Anticipated Base Salary Range
$167,700—$231,800 USD
Canada | Remote - Anticipated Base Salary Range
$159,000—$193,000 CAD
Responsibilities
Lead end-to-end development of machine learning models, from problem formulation and experimentation through deployment and performance evaluation
Design and evaluate advanced modeling approaches to improve predictive accuracy, robustness, and operational effectiveness
Identify opportunities to improve existing models through feature development, experimentation, and rigorous statistical analysis
Partner with engineering, product, and business stakeholders to translate complex requirements into measurable machine learning objectives
Guide technical decisions, review scientific methodologies, and share expertise to improve the quality and effectiveness of the team's work
Requirements
Bachelor’s degree in Computer Science, Engineering, Mathematics, Statistics, or a related field
PhD in mathematics, applied mathematics, statistics, physics, econometrics, operations research, computer science, or a related quantitative field (preferred)
Fine-tunes Large Language Models with emphasis on instruction fine-tuning and domain adaptation to enhance model relevance and performance in specific contexts.
Responsibilities
Perform independently and become an SME
Active participation/contribution in team discussions
Contribute in providing solutions to work related problems
Collaborate with team members to identify areas for model improvement and optimization
Conduct experiments to evaluate model performance and implement necessary adjustments
AI Architect with 6–9 years of overall IT experience, including 3–4 years of hands‑on experience in Artificial Intelligence, Machine Learning, or Generative AI solutions.
Responsibilities
Design end‑to‑end AI solutions across data, model, application, and infrastructure layers.
Translate business problems into AI‑driven technical architectures.
Define AI platform architecture, model deployment strategies, and integration patterns.
Evaluate and select appropriate AI/ML frameworks, tools, and technologies.
Provide architecture guidance for AI initiatives across the organization.
Requirements
Bachelor’s Degree in Engineering (Computer Science or Information Technology)
Nice to have: enterprise AI platform implementation
Nice to have: vector databases (Pinecone, FAISS, Weaviate, etc.)
Nice to have: AI observability and monitoring tools
We are seeking an AI Architect with 6–9 years of overall IT experience, including 3–4 years of hands-on experience in Artificial Intelligence, Machine Learning, or Generative AI solutions. The ideal candidate will have a strong full stack engineering background combined with expertise in designing, developing, and deploying AI-powered systems at scale.
Responsibilities
Design end-to-end AI solutions across data, model, application, and infrastructure layers
Translate business problems into AI-driven technical architectures
Define AI platform architecture, model deployment strategies, and integration patterns
Design and implement machine learning and deep learning solutions where required
Architect and develop Generative AI applications including LLM integrations, Retrieval-Augmented Generation (RAG), prompt engineering frameworks, and AI agents
Requirements
Bachelor’s Degree in Engineering (Computer Science or Information Technology)
Nice to have: enterprise AI platform implementation
Nice to have: vector databases
Nice to have: AI observability and monitoring tools
Seeking an AI Architect with 9+ years of overall IT experience, including 3–4 years of hands-on experience in Artificial Intelligence, Machine Learning, or Generative AI solutions, to define AI architecture strategies and integrate AI capabilities into enterprise applications.
Responsibilities
Design end-to-end AI solutions across data, model, application, and infrastructure layers
Translate business problems into AI-driven technical architectures
Define AI platform architecture, model deployment strategies, and integration patterns
Design and implement machine learning and deep learning solutions
Architect and develop Generative AI applications including LLM integrations, Retrieval-Augmented Generation (RAG), prompt engineering frameworks, and AI agents
Requirements
Bachelor’s Degree in Engineering (Computer Science or Information Technology)
Nice to have: Enterprise AI platform implementation
Nice to have: Vector databases (Pinecone, FAISS, Weaviate)
Nice to have: AI observability and monitoring tools
We are seeking an AI Architect with 6–9 years of overall IT experience, including 3–4 years of hands-on experience in Artificial Intelligence, Machine Learning, or Generative AI solutions. The ideal candidate will have a strong full stack engineering background combined with expertise in designing, developing, and deploying AI-powered systems at scale.
Responsibilities
Design end-to-end AI solutions across data, model, application, and infrastructure layers
Translate business problems into AI-driven technical architectures
Define AI platform architecture, model deployment strategies, and integration patterns
Design and implement machine learning and deep learning solutions where required
Architect and develop Generative AI applications including LLM integrations, Retrieval-Augmented Generation (RAG), prompt engineering frameworks, and AI agents
Requirements
Bachelor’s Degree in Engineering (Computer Science or Information Technology)
Nice to have: enterprise AI platform implementation
Nice to have: vector databases
Nice to have: AI observability and monitoring tools
We are seeking an AI Architect with 6–9 years of overall IT experience, including 3–4 years of hands-on experience in Artificial Intelligence, Machine Learning, or Generative AI solutions. The ideal candidate will have a strong full stack engineering background combined with expertise in designing, developing, and deploying AI-powered systems at scale.
Responsibilities
Design end-to-end AI solutions across data, model, application, and infrastructure layers
Translate business problems into AI-driven technical architectures
Define AI platform architecture, model deployment strategies, and integration patterns
Evaluate and select appropriate AI/ML frameworks, tools, and technologies
Provide architecture guidance for AI initiatives across the organization
Requirements
Bachelor’s Degree in Engineering (Computer Science or Information Technology)
Nice to have: Enterprise AI platform implementation
Serve as the technical authority driving the convergence of Artificial Intelligence, silicon/hardware design analysis, and systems engineering
Architect and build generative AI tools, foundation model skills, and agentic workflows by leveraging complex ASIC architectural specifications, system schematics, software contracts, and historical test execution telemetry
Transform how hardware diagnostic software is created, optimized, and deployed across Google’s next-generation compute, accelerator (TPU/GPU), network, and storage infrastructure
Empower Diagnostic Software Engineers to achieve comprehensive test coverage across all hardware components, interfaces, and functional blocks
Optimize test execution time and pinpoint optimal repair actions using advanced artificial intelligence systems
Requirements
Bachelor’s degree or equivalent practical experience
Nice to have: Master’s degree in Computer Science
Nice to have: Master’s degree in Electrical/Computer Engineering
Nice to have: Master’s degree in Artificial Intelligence
The Research Data Scientist will assist faculty with the use of technology and cutting‑edge data science in research, building and optimizing LLM‑based text processing and multimodal video generation pipelines, conducting model evaluation and testing, and supporting deployment of a secure patient‑facing interface.
Locations (3)
Chicago, Illinois, United States
London, England, United Kingdom
Hong Kong, China
Compensation
$69,000.00 - $72,000.00
Responsibilities
Implements and maintains components of the LLM‑based text‑to‑video pipeline.
Develops and tests prompting, fine‑tuning, and structured extraction workflows.
Supports integration of text processing systems with video generation tools.
Develops guardrails and evaluation metrics for factual consistency, uncertainty communication, and clinical reliability.
Cross-disciplinary AI Engineer supporting wet-lab discovery research in cell therapy and oncology.
Compensation
The annual base pay for this position ranges from $124K to $187K. Our positions offer eligibility for various incentives—an opportunity to receive short-term incentive bonuses, equity-based awards for salaried roles and commissions for sales roles.
Responsibilities
Partner with experimental scientists to understand key scientific questions, assay workflows, and experimental decision points.
Translate wet-lab problems into AI and data science opportunities.
Build, adapt, and apply AI/ML models to support discovery activities.
Work across diverse biological datasets such as flow cytometry, single-cell and bulk omics, imaging, functional assay readouts, vector characterization data, metadata, and experimental annotations.
Develop data pipelines and analytical frameworks to improve data quality, accessibility, interoperability, and reuse.
Requirements
Bachelor’s in computer science, machine learning, computational biology, bioinformatics, biomedical engineering, systems biology, applied mathematics, or a related field.
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