Lead Engineer

7 - 9 years

0 Lacs

Posted:1 day ago| Platform: Linkedin logo

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On-site

Job Type

Full Time

Job Description

About Biz2X



Biz2X is the leading digital lending platform, enabling financial providers to power growth with a modern omni-channel experience, best-in-class risk management tools and a comprehensive yet flexible Servicing engine. The company partners with financial institutions to support their Digital Transformation efforts with Biz2X’s digital lending platform. Biz2X solutions not only reduces operational expenses, but accelerates lending growth by significantly improving client experience, reducing total turnaround time, and equipping the relationship managers with powerful monitoring insights and alerts


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  • Role – Lead Engineer – AI, Machine Learning


Job O

We are seeking a Lead Engineer to drive the development and deployment of sophisticated AI solutions in our fintech products. You will lead a team of engineers, oversee MLOps pipelines, and manage large language models (LLMs) to enhance our financial technology services.


Key Respons

  • AI/ML Development:

    Design and implement advanced ML models for applications including fraud detection, credit scoring, and algorithmic trading.
  • MLOps:

    Develop and manage MLOps pipelines using tools such as MLflow, Kubeflow, and Airflow for CI/CD, model monitoring, and automation.
  • LLMOps:

    Optimize and operationalize LLMs (e.g., GPT-4, BERT) for fintech applications like automated customer support and sentiment analysis.
  • Technical Leadership

    : Mentor and lead a team of ML engineers and data scientists, conducting code reviews and ensuring best practices.
  • Collaboration:

    Work with product managers, data engineers, and business analysts to align technical solutions with business objectives.
  • Experience in building RA

    G

    pipelines


Qualifications:

Experience: 7-9 years in AI, ML, MLOps, and LLMOps with a focus on fintech.

Technical Skills: Expertise in TensorFlow, PyTorch, scikit-learn, and MLOps tools (MLflow, Kubeflow). Proficiency in large language models (LLMs) and cloud platforms (AWS, GCP, Azure).

Strong programming skills in Python, Java, or Scala.

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