Senior ML Engineer

4 weeks ago

Bengaluru, India Awign Expert Full time

Job Title: Senior Machine Learning Engineer

Experience: 3 - 5 years

Joining: Immediate

Location: Bengaluru, Karnataka


Key Responsibilities:

1. End-to-End ML Solutions: Take full ownership of developing end-to-end machine

learning solutions within the geospatial domain, focusing on image data, point cloud

data, geophysical data, geological data, and related datasets, within the GIS context

and ensuring alignment with customer needs and company objectives.

2. Technical Collaboration: Collaborate closely with development teams, translating

geospatial requirements into technical specifications for seamless integration with

the product.

3. GIS Integration: Work collaboratively with GIS experts to integrate machine learning

solutions into GIS systems, gradually gaining proficiency in GIS tools and libraries.

4. Data Preprocessing: Develop and refine preprocessing pipelines for geospatial data,

ensuring data quality and normalization.

5. Collaboration and Knowledge Transfer: Collaborate with GIS and remote sensing

experts, leveraging their knowledge and gradually acquiring expertise in the GIS

domain.

6. Continuous Learning: Stay updated on the latest advancements in machine learning

and GIS technology, actively participating in training programs and self-directed

learning.

7. Documentation and Reporting: Document progress, methodologies, and outcomes

for knowledge transfer and future reference.


Requirements:

1. 3+ years of hands-on experience in machine learning engineering or related technical

roles.

2. Proven ability to engage with technical teams, translating geospatial requirements

into machine learning specifications.

3. Strong background in algorithm development, model training, and deployment.

Experience with GIS-related data is a plus.

4. Expertise in Python and machine learning frameworks (e.g., TensorFlow, PyTorch).

5. Solid understanding of image analysis, and point cloud processing.

6. Excellent analytical and problem-solving skills, with a data-driven decision-making

approach.

7. Effective verbal and written communication skills, capable of conveying complex

technical concepts clearly.

8. Demonstrated ability to work collaboratively with cross-functional teams, including

development, design, and marketing.

9. Comfortable working in a fast-paced environment, adaptable to changing technical

priorities and requirements.


Ideal Candidate should have: 1. The ideal candidate will have expertise in a variety of deep learning techniques including Vision Transformers, Convolutional Neural Networks (CNNs), and Deep Neural Networks (DNNs).
2. Familiarity with object detection frameworks such as YOLO (You Only Look Once) and region-based CNNs like R-CNN.
3. Experience with image segmentation techniques for tasks such as semantic segmentation, instance segmentation, and panoptic segmentation.
4. Ability to work with point cloud data and apply relevant algorithms for tasks like 3D object detection and semantic segmentation.
5. Proficiency in deploying and fine-tuning popular deep learning models like DenseNet and ResNet for specific applications.

Please Note: 
Salary: As per Market Standard

Education: BE/Btech (Computer Science)
Preferred candidates from Tier 1 colleges
Candidates from Tier 2 or lower institutions should have a minimum GPA of 8 from their respective colleges

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