Machine Learning Engineer

1 day ago


Bengaluru, Karnataka, India Deloitte Full time ₹ 12,00,000 - ₹ 36,00,000 per year

Dear Candidates,

We are looking for candidates interested in the role of Machine Learning Engineer.

Following is the Job Description for your reference.

Job Title:
Machine Learning Engineer

Location:
Bangalore/Gurugram/Chennai

Experience:
8–10 Years

Domain:
Payments / FinTech (preferred)

About the Role

We are looking for a seasoned
Machine Learning Engineer
with 8–10 years of experience to join our team. The ideal candidate will have a strong foundation in machine learning, deep learning, data science, and model deployment at scale. Experience in the
payments domain
, especially working with
credit card and UPI data
, is highly desirable.

Key Responsibilities

  • Collect, preprocess, and analyze credit card and UPI payment data to extract features and insights.
  • Design and develop ML models for use cases such as
    fraud detection
    ,
    transaction risk scoring
    , and
    customer analytics
    .
  • Build, fine-tune, and deploy
    OSS LLMs
    (Open-Source Large Language Models) like GPT, T5, BERT, Falcon, and Vision Transformers for tasks such as:
  • Text summarization
  • Synthetic data generation
  • NLP applications in payments
  • Implement, monitor, and maintain ML/GenAI models in production environments using
    MLOps tools
    (MLflow, Kubeflow, AWS SageMaker, Comet OPIK).
  • Evaluate model performance using industry-standard metrics (Precision, Recall, F1-score, AUC-ROC).
  • Collaborate with cross-functional teams to align ML solutions with business objectives.
  • Monitor model drift, performance, and ensure scalability and reliability of production systems.

Required Skills

  • 8–10 years of experience in ML engineering, data science, or related roles.
  • Proficient in
    Python
    (must), and working knowledge of
    R
    and
    Java
    .
  • Solid understanding of
    machine learning
    ,
    statistics
    , and
    data science
    principles.
  • Experience with data processing tools such as
    SQL
    ,
    Spark
    , and
    Hadoop
    .
  • Strong hands-on experience with frameworks:
  • TensorFlow
    ,
    PyTorch
    ,
    Scikit-learn
  • Hugging Face Transformers
    ,
    LangChain
    ,
    LlamaIndex
  • Familiarity with
    foundational models
    : BERT, GPT, T5, ViT, etc.
  • Exposure to
    GenAI
    and
    OSS LLM fine-tuning & deployment
    .
  • Hands-on experience with
    Docker
    ,
    Kubernetes
    , and production deployment of ML models.
  • Hands-on & strong in Python programming (note: Candidate is expected to complete a coding exercise during the interview)
  • Building
    Agentic solutions
    & exposing the same Agents as Services
  • Building chat-bots based on
    RAG framework
  • Experience in optimizing prompts
  • Excellent communication and presentation skills.

Preferred Qualifications

  • Background in the
    payments or financial domain
    (UPI, credit card data).
  • Experience working with
    fraud detection
    ,
    customer segmentation
    , or
    risk scoring models
    .
  • Experience with model monitoring, feedback loops, and model retraining pipelines.

Those who are interested kindly apply on the following link,



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