Top AI & Machine Learning Jobs

Uses advanced analytics, business intelligence, and data science to deliver strategic insights and solutions for AML and sanctions clients in banking and capital markets. Responsibilities include analyzing complex datasets, developing data pipelines and architecture, creating scalable visualization solutions, collaborating with teams, managing stakeholders, building client relationships, and solving complex problems. The role also involves mentoring and managing others while maintaining professional and technical standards.

Develop and maintain AI-powered full-stack applications across frontend, backend, APIs, databases, and cloud environments. Integrate AI services and automation into enterprise workflows, build secure data pipelines and retrieval systems, apply natural language processing, and support deployment, monitoring, and maintenance. Collaborate with business and technical stakeholders to deliver solutions for risk, compliance, audit, and forensics clients while ensuring data quality, security, and regulatory compliance.

Develop and implement generative AI solutions for client engagements, including contact center applications, machine learning and NLP integrations, prompt engineering, LLM evaluation, and LLMOps governance. Use Python, Azure AI Services, Google Vertex AI, LangChain, and LLM APIs to build, deploy, monitor, and refine AI applications while supporting data analytics and client outcomes.

Design and deploy AI/ML systems: build data pipelines, develop models using Python and TensorFlow, integrate diverse data sources, apply NLP and sentiment analysis, conduct complex data analysis, and collaborate with cross-functional teams to deliver scalable client solutions while continuously learning.

Develop and optimize AI and machine learning algorithms, models, and scalable Python systems. Transform raw data into actionable insights, apply machine learning libraries and NLP techniques, improve data quality, and deliver automation solutions for clients. The role also involves complex data analysis, stakeholder collaboration, client relationship management, and navigating ambiguous business challenges.

Leads teams in designing and deploying scalable AI and machine learning solutions for consulting clients. Responsibilities include data wrangling, complex analysis, data modeling, AI system implementation, data pipeline and infrastructure oversight, deep learning, neural networks, data quality validation, and stakeholder collaboration. The manager coaches team members, manages performance, supports innovation, and applies Python, Java, and cloud technologies to build production-ready AI applications.

Design, build, and deploy scalable AI and ML solutions by wrangling and integrating data, implementing models (Python/Java, TensorFlow, Scikit-Learn), developing data pipelines and NLP applications, collaborating with clients, and mentoring junior team members to drive business insights and regulatory risk solutions.

Design, build, and deploy AI and machine learning solutions at scale. Develop data pipelines and scalable models, perform data wrangling and analysis, apply NLP and neural networks, collaborate with clients and teams, and contribute to open-source and iterative improvement of AI systems.

Lead design and implementation of enterprise AI architectures and integration solutions, manage multiple projects and executive client relationships, drive strategic technology planning and business development, mentor teams, conduct market research and feasibility studies, and promote technological innovation across the firm.

Lead and manage a software engineering team to design, build, test, and deploy AI-enabled applications (LLM integrations, RAG, APIs). Own project planning, budgeting, CI/CD, code quality, observability, microservices, and cross-functional collaboration while coaching and developing team members.