Senior Machine Learning Engineer

Senior ML Engineer

Experience: 4+ years | Location: Bengaluru (Hybrid)

Akaike Technologies is a dynamic and innovative AI-driven company dedicated to building impactful solutions. Our mission is to empower businesses by harnessing the power of data and AI to drive growth, efficiency, and value. We foster a culture of collaboration, creativity, and continuous learning.

Job Description: Focus on PySpark, Databricks & Real-time ML Pipelines

We are seeking an experienced and highly skilled
Senior Data Scientist
to join our team in Bengaluru. This role focuses on driving innovative,
large-scale
solutions using cutting-edge Classical Machine Learning,
PySpark
,
Spark SQL
, and Generative AI. The ideal candidate will possess a blend of deep technical expertise, strong business acumen, effective communication skills, and a sense of ownership. We require a proven track record in designing, developing, and
real-time deploying scalable ML/DL pipelines
and
LLM Agents
in a fast-paced, collaborative environment.

Key Responsibilities: Emphasizing Data and Deployment

Large-Scale Data Handling, PySpark, & Databricks Deployment

• Efficiently handle and model
  billions of data points
  using multi-cluster data processing frameworks (
  PySpark
  ,
  Spark SQL
  ).

Expertise on Databricks is a must have:
Ability to design, write, scale, and monitor
end-to-end ML Pipelines
on Databricks.

• Proven expertise to run and manage
  Databricks data pipelines in real time
  for low-latency decision-making.
• Design and implement high-performance
  API's using FastAPI
  in Python to expose real-time and batch ML pipelines.

ML/DL & GenAI Solution Development & Deployment

• Design, implement, and deploy end-to-end ML/DL, GenAI solutions, writing
  modular, scalable, and production-ready code
  .
• Develop and implement scalable deployment pipelines using
  Docker
  and AWS services (
  ECR, Lambda, Step Functions
  ).
• Design and implement custom models and loss functions to address data nuances and specific labeling challenges.
• Apply specialized modeling for marketing scenarios (Targeting, Budget optimisation, Churn) and data limitations (
  Sparse/incomplete labels, Single class learning
  ).

Generative AI & Large Language Models (LLM Agents)

• Leverage in-depth understanding of
  Transformer architectures
  and the principles of Large and Small Language Models.
• Practical experience in building
  LLM-ready Data Management layers
  for large-scale structured and unstructured data.
• Apply foundational understanding of
  LLM Agents
  and multi-agent systems (e.g.,
  Agent-Critique, ReACT
  , Agent Collaboration), advanced prompting, LLM evaluation,
  confidence grading
  , and
  Human-in-the-Loop systems
  .

Must-Have Skills: Core Technical Requirements

Data Pipelines, PySpark & Databricks

• Proficiency in Python
  and its data science ecosystem (NumPy, Pandas, Dask,
  PySpark
  ) for
  large-scale data processing
  .
• Expert, hands-on experience with Databricks
  for MLOps, pipeline orchestration, and real-time deployment.
• Ability to perform effective feature engineering by understanding complex business objectives.

Core Machine Learning & Deep Learning

• In-depth knowledge of ANN, 1D/2D/3D
  Convolutional Neural Networks (ConvNets)
  , LSTMs, and
  Transformer models
  .
• Strong proficiency in
  PU learning
  ,
  single-class learning
  , and
  representation learning
  , alongside traditional ML approaches.
• Advanced understanding and application of
  model explainability techniques
  (e.g., SHAP, LIME).
• Hands-on experience with ML/DL libraries such as Scikit-learn,
  TensorFlow/Keras, and PyTorch
  .

GenAI Models

• Experience utilizing large-scale language models (GPT-4, Mistral, Llama, Claude) through
  prompt engineering
  and custom
  finetuning
  .

Relevant to Have

• Awareness of best software design practices and backend frameworks like Flask.
• Knowledge of Recommender Systems and advanced learning techniques (Representative learning, PU learning).

Benefits and Perks

Competitive ESOP grants.

Support for publishing papers and attending academic/industry conferences.

High visibility across all functions at Akaike.