Applied Scientist focused on causal inference, statistics, and machine learning to optimize marketing channels and product performance within Apple Services.
Responsibilities
Design, develop, and deploy causal inference and AI/ML solutions for marketing effectiveness
Define technical vision, strategy, and roadmap for AIML initiatives
Collaborate with cross-functional partners to deliver customer and business value
Requirements
Master’s degree in Statistics, Economics, Mathematics, Machine Learning, Computer Science, Engineering, or a related technical field
Nice to have: PhD in related field
Nice to have: Hands‑on experience leveraging Generative AI to improve productivity and generate new insights
Lead the development and execution of AI and machine learning strategy for biometric face verification and security.
Compensation
Comp: Negotiable (Base) + Company Performance Bonus (20%) + EMI Share Options + UK iProov Benefits
Responsibilities
Define and steward the AI strategy, roadmap, and vision across core AI research, product, and production domains
Lead teams across research, production/engineering, and MLOps to deliver robust, secure, explainable models for liveness assurance and fraud detection
Oversee model development and deployment pipelines: data ingestion, training, optimization, evaluation, monitoring, and continuous improvement in adversarial biometric threat landscapes
Ensure AI is aligned with product and commercial goals, measuring ROI and outcomes of AI deployments
Drive partnerships and external collaboration with academic, industry, and regulatory stakeholders
Requirements
Master’s or PhD in computer science, machine learning, data science, or a AI related field
Lead AI/ML solution design, development, deployment, and lifecycle management for scalable, production‑ready models.
Responsibilities
Execute end‑to‑end development of AI/ML systems
Provide architectural direction for ML platforms
Lead evaluation and integration of AI technologies
Collaborate with product and domain teams on ML roadmaps
Oversee ML model lifecycle management
Requirements
Bachelor’s or master’s degree in computer science, Data Science, Engineering, or a related technical field; master’s degree in data science is preferable
Lead AI engineering teams at Blue Cross Blue Shield of Massachusetts, driving technical excellence, mentoring engineers, and building production‑grade agentic AI systems for healthcare.
Locations (2)
Boston, Massachusetts, United States
Hingham, Massachusetts, United States
Compensation
Salary Range: $151,200.00 - $184,800.00
Responsibilities
Provide technical leadership and mentorship to AI engineers
Lead solution design for agentic AI systems, generative AI integrations, and RAG architectures
Collaborate with product owners to refine requirements and deliver features on time
Build scalable AI systems and manage performance, reliability, and monitoring
Troubleshoot complex ML pipeline and cloud infrastructure issues
Requirements
Bachelor's degree in Computer Science, Engineering, Technology, or a related field
Design, build, and optimize AI/ML pipelines for real‑time and batch inference
Collaborate with data engineers and software developers to integrate models into TymeX's banking platform
Research, prototype, and productionize models in areas such as credit scoring, fraud detection, transaction classification, personalization, and conversational AI
Implement robust model evaluation, A/B testing, and drift detection frameworks
Contribute to internal frameworks and libraries to standardize ML development workflows
Build and maintain machine learning systems and models for MoneyLion’s products, leading automation, architecture, and best practices for the Data Science team.
Responsibilities
Frame and contextualize machine learning problems
Research, build and design machine learning systems and models
Assess and analyze data for modelling
Identify, prototype and implement machine learning algorithms
Design, execute and monitor model experiments and metrics
Requirements
Nice to have: MLOps tools such as DVC, MLFlow, Metaflow, Seldon, BentoML
Nice to have: Experience building ML systems and workflows
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