357 Machine Learning Specialists jobs in Delhi

Job Title: H&E Image Analysis Scientist / Machine Learning Engineer- Spatial Omics (PhD)

Experience: Freshers

Location: Delhi

Job Description:

We are seeking a motivated PhD candidate interested in machine learning for histopathology

image analysis. The candidate will contribute to developing and optimizing deep learning

models to analyze digitized H&E slides for cancer classification and spatial mapping. This

role is well-suited for researchers aiming to apply advanced computational methods to

biomedical challenges.

Responsibilities:

● Design, develop, and train convolutional neural networks (CNNs) and related ML

models on H&E-stained histology images.

● Use and extend tools such as QuPath for cell annotations, segmentation models, and

dataset curation.

● Preprocess, annotate, and manage large image datasets to support model training

and validation.

● Collaborate with cross-disciplinary teams to integrate image-based predictions with

molecular and clinical data.

● Analyze model performance and contribute to improving accuracy, efficiency, and

robustness.

● Document research findings and contribute to publications in peer-reviewed journals.

Qualifications:

● PhD in Computer Science, Biomedical Engineering, Data Science, Computational

Biology, or a related discipline.

● Demonstrated research experience in machine learning, deep learning, or biomedical

image analysis (e.g., publications, thesis projects, or conference presentations).

● Strong programming skills in Python and experience with ML frameworks such as

TensorFlow or PyTorch.

● Familiarity with digital pathology workflows, image preprocessing/augmentation, and

annotation tools.

● Ability to work collaboratively in a multidisciplinary research environment.

Preferred:

● Background in cancer histopathology or biomedical image analysis.

● Knowledge of multimodal data integration, including spatial transcriptomics.

InnerGize
is a consumer health and wellness platform that uses wearable patches to help people manage stress, sleep and mental performance. We are building algorithms that make our product more accurate and user-friendly.

We are looking for a
Machine Learning Engineer
with 2–4 years of experience to design and deploy
convolutional neural network (CNN) algorithms
that can detect and validate correct patch placement based on sensor data.

This position focuses on developing and refining CNN-based models from data collection through to deployment.

Job Requirements

:

• Design, train, and optimize CNN architectures for correct wearable patch placement detection using available sensor data.
• Build and maintain data pipelines for collection, labeling, augmentation, and validation of training datasets.
• Evaluate model performance and iterate to improve accuracy and robustness across users.
• Prepare models for deployment on mobile or embedded systems (optimizing for latency and size).
• Document experiments, models, and performance metrics clearly for internal teams.
• Collaborate with data, product and firmware teams to integrate model outputs into the InnerGize ecosystem.

Education Requirements:

• B.Tech / B.E. in Computer Science or a related field with specialization in Machine Learning, OR
• Master's / Ph.D. in Machine Learning, Data Science, or Applied Mathematics (preferred).
• Experience:
• 2–4 years of professional experience developing machine learning models, with a strong focus on CNN architectures.
• Technical Skills:
• Proficiency in Python and frameworks such as PyTorch or TensorFlow.
• Demonstrated experience designing, training, and deploying CNNs for classification or regression tasks.
• Ability to work with real-world datasets, including preprocessing and augmentation.
• Familiarity with on-device or edge deployment tools such as TensorFlow Lite or ONNX (a plus).
• Soft Skills:
• Strong analytical and problem-solving skills.
• Good communication and documentation abilities.
• Comfortable working cross-functionally with other teams.

Preferable Skills:

• Exposure to time-series or sensor-based data.
• Understanding of mathematical/statistical models for signal behavior.
• Prior experience deploying models on constrained devices.

CTC:
₹12–18 LPA
, commensurate with experience and expertise.

Job Description – NLP Expert (Transformers & Custom Architectures)

Position:
NLP Expert

Experience Required:
5
+ Years

Location:
New Delhi (Onsite)

Domain Focus:
Defence Technology & Naval Applications

About Us

At
Crimson Energy Experts Pvt. Ltd.
, we are developing advanced defence-grade software systems to strengthen the future of India's naval and maritime operations. Our projects focus on
Defence Technology, Artificial Intelligence, and Advanced Analytics
, with a mission to empower the
Indian Navy
through next-generation NLP, AI, and data-driven decision-making.

We are looking for an
NLP Expert
with deep expertise in
Hugging Face Transformers
and hands-on experience in
pretraining and developing custom encoding architectures
. This role is critical to building
domain-specific language models
for secure and high-performance defence applications.

Key Responsibilities

• Pretrain and fine-tune
  Hugging Face Transformers
  for
  naval and defence-specific use cases
  .
• Design and implement
  custom encoding architectures
  for unstructured defence data (text, intelligence reports, maritime logs, etc.).
• Develop
  domain-specific embeddings
  and representations for secure and reliable software applications.
• Build
  end-to-end NLP pipelines
  : data collection, preprocessing, model training, evaluation, and deployment.
• Collaborate with engineers and defence domain experts to align NLP solutions with
  operational requirements
  .
• Optimize models for
  performance, scalability, and low-latency inference
  in mission-critical environments.
• Ensure all solutions comply with
  security, confidentiality, and defence-grade standards
  .

Required Skills & Qualifications

• 4+ years
  of experience in
  Natural Language Processing (NLP)
  and
  Deep Learning
  .
• Strong expertise with
  Hugging Face Transformers
  (BERT, GPT, RoBERTa, LLaMA, etc.).
• Experience in
  pretraining LLMs
  and creating
  custom tokenizers/encoding architectures
  .
• Proficiency in
  Python
  , PyTorch, and TensorFlow.
• Solid background in
  text representation learning, embeddings, and sequence modeling
  .
• Experience in
  distributed training
  (multi-GPU/TPU setups).
• Familiarity with
  MLOps practices
  for deploying and monitoring NLP systems.
• Ability to design solutions with
  security-first principles
  for sensitive defence applications.

What We Offer

• An opportunity to
  build indigenous NLP systems
  for the
  Indian Navy
  .
• Work on
  cutting-edge NLP & AI projects
  that directly impact national security.
• Competitive pay with performance-driven growth.
• A chance to be part of a
  mission-driven team
  solving real-world defence challenges.