Senior Applied AI Research Engineer to join the Research & Development (R&D) team, focusing on hands-on AI research, model development, and experimentation across Computer Vision, LLMs, SFT, RL, and Deep Learning.
Responsibilities
Conduct applied research in Artificial Intelligence, Machine Learning, Deep Learning, Computer Vision, NLP, and emerging AI technologies.
Review, analyze, reproduce, and implement methodologies from academic research papers and open-source research projects.
Design and execute experiments to evaluate AI models, algorithms, training methodologies, and optimization techniques.
Design, develop, train, fine-tune, and optimize deep learning models using frameworks such as PyTorch or TensorFlow.
Research and implement techniques for adapting and fine-tuning Large Language Models and other foundation models.
Requirements
Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Robotics, Mathematics, Electrical Engineering, or a related technical field
Master's degree or PhD in Artificial Intelligence, Machine Learning, Computer Science, Robotics, or a related research-intensive discipline
In this highly visible role, you will work at the intersection of AI, language, and technology to help develop and optimize Large Language Model-based analytics solutions that streamline business operations, improve access to complex data and tools, and enable faster, better-informed decision-making.
Compensation
The estimated base wage range for this position is $35.00-45.00/hr. The individual base wage is based on work location and additional factors, including job-related skills, experience, and relevant education or training.
Responsibilities
Be part of a product team of about 20 data scientists, machine learning engineers, and platform engineers focused on developing and maintaining agentic solutions & machine learning solutions and big data platforms.
Develop and optimize LLM-based analytics and agentic solutions using commercial (e.g., Azure OpenAI) and open-source (e.g., Google Gemma, Qwen) models to transform business operations and streamline daily workflows.
Drive seamless integration of LLM models with existing platforms and enterprise systems.
Build and scale robust data connectors and knowledge bases for agentic systems.
Design, architect, develop, and manage a state-of-the-art enterprise agentic AI platform to support scalable business solutions.
Research interns will contribute to fundamental and applied research in artificial intelligence and machine learning, developing novel algorithms, models, and systems that advance the state of the art.
Compensation
$178,200.00 - $267,400.00
Responsibilities
Conducting original research, developing novel machine learning algorithms and architectures, and designing, training, and evaluating AI models to advance the state of the art.
Developing efficient AI systems and software frameworks, including optimization for mobile, edge, and cloud platforms.
Exploring emerging computing paradigms, including hardware-software co-design, compute-in-memory, and distributed or federated learning.
Collaborating with researchers and engineers to prototype, validate, and communicate research findings, with opportunities to contribute to scientific publications and technology transfer.
Requirements
Master's degree in Computer Engineering, Computer Science, Electrical Engineering, or related field
PhD in Computer Engineering, Computer Science, Electrical Engineering, or related field
Review code developed by other developers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
Participate in, or lead design reviews with peers and stakeholders to decide amongst available technologies.
Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
Requirements
Bachelor’s degree or equivalent practical experience.
Help define and develop the analytical directions that support our needs for assessing and managing the credit risks associated with granting loans and the financing product lifecycle.
Compensation
Competitive salary and annual bonus
Responsibilities
Design, apply, implement and develop decision-making strategies in the realm of credit risk management
Develop, calibrate and roll out predictive models and advanced machine learning algorithms to improve the performance of risk strategies and the experience of our members and clients
Maximize the financial impact of strategies that have been rolled out
Lead or contribute to large-scale strategic transformation initiatives that require advanced expertise in data science, predictive modelling and credit risk
Prepare and present the methodological files, analyses and recommendations required for various governance processes
Requirements
Bachelor’s degree in math, statistics, economics, finance or a related field
As a Senior Data Scientist, Credit Risk Strategy, you help define and develop the analytical directions that support our needs for assessing and managing the credit risks associated with granting loans and the financing product lifecycle.
Compensation
Competitive salary and annual bonus
Responsibilities
Design, apply, implement and develop decision-making strategies in the realm of credit risk management
Develop, calibrate and roll out predictive models and advanced machine learning algorithms
Maximize the financial impact of strategies that have been rolled out
Lead or contribute to large-scale strategic transformation initiatives
Prepare and present the methodological files, analyses and recommendations required for various governance processes
Requirements
Bachelor’s degree in math, statistics, economics, finance or a related field
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