Senior Machine Learning Engineer

Posted 15 Days Ago
Be an Early Applicant
2 Locations
In-Office
55K-65K Annually
Mid level
Fintech • Cybersecurity
The Role
The Senior Machine Learning Engineer will develop and deploy AI solutions, maintain machine learning models, optimize performance, and support integration with existing systems.
Summary Generated by Built In

Liminal is a global market intelligence and strategic advisory firm specializing in digital identity, financial crime and compliance, and IT security technology solutions across industries while also catering to the private equity and venture capital community. Founded in 2016, Liminal offers strategic and analytical services supporting executive decision-making at all product and business lifecycle stages. We advise some of the world’s most prominent business leaders, investors, and policymakers on building, acquiring, and investing in the next generation of solutions and technologies. We provide access to proprietary data and analysis, strategic frameworks, and integrated insights on the industry’s only market intelligence platform. 


Every major company in the world has started focusing on the next generation of digital identity technologies as a necessity for continued growth and security. Our team works with a myriad of organizations, from Fortune 100s to startups, across industries including financial services, technology, telecommunications, and the P2P economy. At Liminal, we help businesses build solutions, execute strategies, invest intelligently, and connect with key decision-makers. We know that it’s in the sharing of discovery and insights that groundwork is laid, problems are solved, and entire sectors advance at the speed of light. Keeping information to ourselves delays progress for all. At Liminal, we don't just respond to the market; we define it.

About the role

This role focuses on the end-to-end lifecycle of AI and machine learning solutions, from ideation and development to deployment and ongoing maintenance of production-grade systems. Reporting to the AI Solutions Architect and partnering closely with the Chief Product Officer and Chief Innovation Officer, the Senior Machine Learning Engineer will play an important role in building scalable, robust, and efficient AI-driven software solutions. This individual must be able to bridge exploratory projects with production systems, ensuring seamless transitions and operational excellence.

What you'll do

  • AI Solution Development and Deployment:
    • Collaborate with cross-functional teams to define and design AI solutions aligned with business objectives.
    • Build, deploy, and maintain production-grade machine learning models and systems that drive efficiency and innovation across multiple departments.
    • Ensure AI solutions meet performance, scalability, and reliability standards in a production environment.
  • Model Optimization and Maintenance:
    • Continuously improve machine learning models through fine-tuning, retraining, and incorporating new data and feedback.
    • Monitor and optimize the performance of deployed models and systems, implementing updates and resolving issues proactively.
    • Work with the AI Solutions Architect to develop pipelines for automated retraining, testing, and deployment of AI models.
  • Cloud Infrastructure and Integration:
    • Leverage cloud platforms (e.g., AWS, Azure, Google Cloud) for model deployment, orchestration, and monitoring.
    • Implement and manage robust infrastructure to support AI applications, ensuring scalability and fault tolerance.
  • Pipeline Development and Data Engineering:
    • Develop and maintain data pipelines for efficient data ingestion, preprocessing, and feature engineering.
    • Support integration of AI models into existing software systems, collaborating with product and engineering teams.
  • Exploratory Analysis and Proof of Concept Development:
    • Conduct exploratory analyses to identify opportunities for AI innovation.
    • Design and prototype solutions, validating feasibility through proof of concept (PoC) projects.
    • Work closely with cross-functional stakeholders to develop experimental projects and transition them into fully developed systems.
  • Performance Monitoring and Troubleshooting:
    • Implement monitoring tools to track model performance, system reliability, and data integrity.
    • Diagnose and address issues in deployed solutions, ensuring minimal downtime and consistent results.
  • Documentation and Compliance:
    • Maintain comprehensive documentation of workflows, models, and system designs to support transparency and collaboration.
    • Adhere and enforce existing organizational standards.

Qualifications

  • 3+ years of experience in ML/AI development including production-environment deployments
  • Bachelor's degree or higher in a relevant field.
  • Proficiency in Python and its machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
  • Hands-on experience with data pipeline development, including data ingestion, preprocessing, and feature engineering.
  • Experience with large language models (LLMs) and natural language processing (NLP), including prompt engineering and fine-tuning techniques.
  • Knowledge of advanced methods such as Retrieval-Augmented Generation (RAG) and platforms like OpenAI or Hugging Face.
  • Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud).
  • Excellent problem-solving skills and ability to troubleshoot and optimize complex AI systems.
  • Strong communication skills to work effectively with technical and non-technical stakeholders.

Top Skills

AWS
Azure
GCP
Python
PyTorch
Scikit-Learn
TensorFlow
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The Company
HQ: New York, NY
28 Employees
Year Founded: 2016

What We Do

Liminal is a boutique strategy advisory firm serving digital identity, fintech, and cybersecurity clients, and the private equity / venture capital community. Since 2016, we have offered objective, high-impact strategic advice, and analytical services, helping to support clients in crucial business decisions at all stages of the product and business lifecycle. We’ve advised many of the world’s most innovative business leaders, investors, and government officials on building, buying, and investing in the next generation of integrated digital identity platforms and technologies. As a result, our clients trust us to set strategic direction in light of radically evolving ecosystem dynamics, pursue new growth strategies, capitalize on M&A opportunities, and optimize deal flow. We see the solutions to these complex digital challenges not as a ‘what’ but as a ‘how.’ We don’t just tell you about the destination, we show you how to get there.

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