Salary
$120k per year
Location
Hybrid (New York, United States)
Employment
Full-Time
Removed from the employer's board on Nov 7, 2026. First seen by Alion on Nov 6, 2026.
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TekWissen is recruiting for an unnamed client seeking an AI/ML Engineer to build and deploy AI and machine learning solutions for financial services platforms. The role focuses on financial analytics, risk management, fraud detection, investment research, and automation, in collaboration with technology, data science, and business teams.
Responsibilities
- Design, develop, and deploy machine learning models for enterprise financial applications
- Develop AI/ML solutions using Python, TensorFlow, PyTorch, and Scikit-learn
- Build and integrate Generative AI applications using Large Language Models (LLMs)
- Implement Retrieval-Augmented Generation (RAG), vector databases, and prompt engineering
- Develop predictive models for financial risk analysis, fraud detection, and business forecasting
- Build scalable REST APIs and integrate AI models with enterprise applications
- Implement MLOps pipelines for model training, deployment, monitoring, and performance optimization
- Work with structured and unstructured datasets using SQL and Python
- Collaborate with software engineers, data scientists, product managers, and business stakeholders
- Ensure AI solutions meet enterprise security, data privacy, governance, and compliance requirements
Skills
- 5+ years of experience in AI/ML engineering or related software development
- Strong programming experience in Python
- Hands-on experience with Machine Learning algorithms and statistical modeling
- Experience with TensorFlow, PyTorch, or Scikit-learn
- Experience with Generative AI, LLMs, and prompt engineering
- Knowledge of LangChain, LangGraph, or similar frameworks
- Experience with RAG, embeddings, and vector databases
- Strong SQL and database knowledge
- Experience developing REST APIs and microservices
- Cloud experience with AWS, Azure, or GCP
- Knowledge of Docker, Kubernetes, Git, and CI/CD pipelines
- Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, Engineering, or a related field
- Financial services or banking domain experience
- Experience with fraud detection, risk modeling, or financial data analytics
- Knowledge of model governance, explainability, and responsible AI
- Experience with MLflow, Kubeflow, or similar MLOps platforms
- Experience with enterprise-scale AI deployments
Benefits
- Hybrid work, depending on team requirements
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