Senior AI/ML Engineer - Practice Leader

September 14

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Aequilibrium

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Payments • Banking • eCommerce • Mobile App Development • Billing

51 - 200

Description

• Lead the AI practice, providing guidance on AI governance frameworks, usage policies, and best practices for AI implementation. • Act as a thought leader on AI and data strategy, shaping the company’s approach to AI technologies and advising clients on AI adoption. • Develop and maintain backend services and AI-driven financial applications, such as chatbots and machine learning-powered systems. • Design and develop scalable and secure server-side components and APIs (RESTful and GraphQL). • Integrate AI/ML models into financial systems, focusing on performance, accuracy, and scalability. • Leverage Microsoft Azure AI tools, including Cognitive Services, Azure Machine Learning, and integrate AI with Azure Databricks or Synapse Analytics. • Build, train, and deploy machine learning models using AutoML and deep learning frameworks like TensorFlow or PyTorch. • Collaborate with cross-functional teams, including designers, backend developers, and domain experts, to deliver end-to-end AI solutions. • Preprocess and analyze financial data to extract insights and features for AI/ML model development. • Lead efforts to improve software development processes using AI for code generation, error detection, and automated software testing. • Stay informed about the latest advancements in AI/ML, data engineering, and financial industry trends. • Write clean, modular, and well-documented code, and maintain a secure and scalable codebase.

Requirements

• Minimum of 5+ years of experience in data engineering, BI, or similar data-centric roles, with a proven track record of AI/ML development. • Strong proficiency in Python and AI/ML frameworks such as TensorFlow, Hugging Face, or PyTorch. • Extensive experience with backend development using Python, with strong API design skills (REST, GraphQL). • Proven experience with Microsoft Azure AI services, including Cognitive Services, Azure Machine Learning, and integration with Azure Databricks or Synapse Analytics. • Proficiency in building, training, and deploying machine learning models using AutoML and deep learning frameworks. • Strong knowledge of databases (SQL and NoSQL), cloud services (AWS, Azure), and version control systems (e.g., Git). • Strong problem-solving, debugging, and analytical skills, with the ability to process and extract insights from complex financial data. • Ability to lead and shape AI strategy, governance, and best practices within the company and for clients.

Benefits

• Competitive compensation rates • Remote-First Work Culture • Medical, dental, and extended health benefits • Employee referral bonus • Feedback based on regular 1:1s • Team-bonding events • And more perks!