Machine Learning Applied Scientist

Position Overview

We are looking for a seasoned Machine Learning Engineer to join our team focused on developing and scaling automated evaluation and synthetic data generation mechanisms that underpin safety assessments in multiple languages and regions. This role involves creating automated judge models, establishing validation protocols, building performance monitoring tools, and designing scalable analytic and reporting systems. The ideal candidate should have strong machine learning engineering expertise, experience with evaluation and data generation pipelines, and the ability to collaborate closely with domain experts. This position works alongside language specialists and multilingual annotators to ensure the robustness of safety evaluation processes across diverse linguistic environments.

Key Responsibilities

• Develop and train automated judge models capable of reliably scoring AI system outputs for safety and compliance with policies, implementing calibration and agreement metrics to reach human-level performance.
• Design and execute validation frameworks to evaluate accuracy, dependability, and linguistic consistency of automated evaluation tools and detect any bias or failure modes across different markets.
• Create and maintain pipelines for synthetic data generation to enhance evaluation scope, stress test safety limits, and enable assessments in low-resource languages, ensuring data is varied, representative, and benchmarked against human-generated data.
• Build automated workflows for analysis and reporting, minimizing manual effort, enhancing reproducibility, and facilitating rapid safety assessments across markets while integrating with existing dashboards and reporting tools.

Required Qualifications

• Minimum of three years experience in machine learning engineering or applied ML research, with practical skills in building and deploying ML models and pipelines.
• Proficient in Python programming and experienced with ML frameworks such as PyTorch, TensorFlow, and Hugging Face Transformers.
• Experience in training, fine-tuning, and assessing language models or classifiers, including expertise in prompt engineering and model calibration.
• Skilled in constructing automated data processing, evaluation, or monitoring pipelines and comfortable with experimental design and statistical validation of model performance across diverse data subsets.
• Ability to work effectively both independently and collaboratively with minimal supervision, ensuring high organization and attention to detail.
• Experience with synthetic data generation techniques like data augmentation, paraphrasing, and controlled data generation methods.
• Knowledge of multilingual natural language processing, cross-lingual transfer learning, or modeling for low-resource languages.
• Familiarity with evaluation-as-a-service platforms or automated red teaming infrastructures.
• Experience working with distributed computing frameworks such as Spark, Ray, or cloud-based ML solutions.
• Background or interest in AI safety domains including responsible AI, content moderation, or trust and safety.
• Experience in integrating continuous integration and delivery processes for ML model validation and deployment.
• Advanced academic degree (MS or PhD) in Computer Science, Machine Learning, Natural Language Processing, or related fields.

Benefits and Work Environment

• Engagement in innovative and cutting-edge projects.
• Collaboration with a driven and committed team.
• Competitive compensation package.
• Flexible work schedules.
• Comprehensive benefits including medical, vision, and dental insurance.
• Company-sponsored social events.
• Opportunities for professional growth and development.
• Modern, fully-equipped office facilities.

About Grid Dynamics

Grid Dynamics (NASDAQ: GDYN) is a premier technology consulting and engineering service provider specializing in AI, analytics, and product engineering. Founded in 2006 and headquartered in Silicon Valley, Grid Dynamics combines business insight with technological expertise to address complex enterprise challenges and facilitate digital transformation initiatives. With over 8 years of specialized experience in enterprise AI and a broad skill set covering data, cloud, DevOps, modernization, and customer experience, we serve clients worldwide with offices in the Americas, Europe, and India.