Home
Communities
Companies
- Companies
  
  Discover best places to work
- Compare Companies
  
  Compare & find best workplace
- Add Office Photos
  
  Bring your workplace to life
- Add Company Benefits
  
  Highlight your company's perks
Reviews
- Company reviews
  
  Read reviews for 6L+ companies
- Write a review
  
  Rate your former or current company
Salaries
- Browse salaries
  
  Discover salaries for 6L+ companies
- Salary calculator
  
  Calculate your take home salary
- Are you paid fairly?
  
  Check your market value
- Share your salary
  
  Help other jobseekers
Interviews
- Company interviews
  
  Read interviews for 40K+ companies
- Campus placements
  
  Interviews questions for 1K+ colleges
- Share interview questions
  
  Contribute your interview questions
Jobs
Awards

RATE NOW!
- ABECA 2025
  
  RATE NOW!
  
  AmbitionBox Employee Choice Awards - 4th Edition
- ABECA 2024
  
  AmbitionBox Employee Choice Awards - 3rd Edition
- AmbitionBox Best Places to Work 2022
  
  2nd Edition
- AmbitionBox Best Places to Work 2021
  
  1st Edition

Add office photos

Employer? Claim Account for FREE

Aptagrim Consulting

Compare

2.5

based on 6 Reviews

9 Aptagrim Consulting Jobs

AI Engineer

Aptagrim Consulting LLP

2.5

based on 6 Reviews

1-5 years

Hyderabad / Secunderabad

1 vacancy

AI Engineer

Aptagrim Consulting

posted 8d ago

Job Role Insights

Fixed timing

Key skills for the job

Digital Marketing Artificial Intelligence Research Machine Learning Chat Process Computer Vision

+ 3 more

Job Description

As a AI Engineer, you will leverage your extensive experience in computer vision, deep learning, machine learning, AI, and generative AI to develop and deploy advanced AI models and solutions. In this client-facing role, you will manage project implementations, ensuring successful delivery and alignment with client expectations. You will work closely with our data scientists, engineers, product teams, and clients to design and implement state-of-the-art algorithms and systems that solve complex real-world problems.

Key Responsibilities:

1. Deep Learning Model Development:

- Research, design, and develop advanced AI and deep learning models, with a particular emphasis on Generative Adversarial Networks (GANs), Transformers, and other architectures for image segmentation, image generation, and computer vision tasks.

- Implement state-of-the-art algorithms and improve the performance of models in terms of accuracy, robustness, and speed.

- Conduct extensive experiments to explore various model architectures, loss functions, and training techniques to optimize models for specific tasks.

2. Model Training Fine-tuning:

- Develop efficient pipelines for training and fine-tuning models on large-scale image datasets.

- Implement transfer learning, data augmentation, and other advanced techniques to enhance model performance.

- Handle the complexity of multi-model environments and manage the training of different models in parallel, optimizing resources.

3. Image Segmentation Computer Vision Solutions:

- Design and implement novel techniques for image segmentation, including semantic segmentation, instance segmentation, and region-based approaches.

- Apply feature extraction and dimensionality reduction methods to improve model interpretability and effectiveness.

4. Model Validation Evaluation:

- Conduct rigorous model validation, implementing techniques like cross-validation, confusion matrix analysis, precision-recall analysis, and ROC-AUC evaluation.

- Optimize model accuracy and performance by tuning hyperparameters, adjusting architectures, and experimenting with different learning rates, optimizers, and regularization techniques.

- Ensure the model generalization by preventing overfitting, using techniques like dropout, batch normalization, and advanced ensemble methods.

5. Advanced Technical Research:

- Stay on the cutting edge of developments in GANs, deep learning, computer vision, and AI ethics by reading research papers, attending conferences, and experimenting with new tools.

- Experiment with advanced generative techniques like Variational Autoencoders (VAEs), Denoising Diffusion Probabilistic Models (DDPMs), and Transformer-based architectures to push the boundaries of current AI capabilities.

- Explore methods for unsupervised, semi-supervised, and self-supervised learning to leverage unlabelled data and reduce dependency on large labeled datasets.

6. Model Deployment Integration:

- Develop scalable model pipelines for deploying trained models into production environments, ensuring efficiency and compatibility with real-time systems.

- Work closely with DevOps teams to containerize models using Docker, manage versions with Git, and deploy models on cloud platforms (AWS, GCP, Azure).

- Ensure seamless integration of AI models into existing systems and workflows, collaborating with software engineering teams to enable real-time inferences and predictions.

7. Collaboration Knowledge Sharing:

- Work closely with cross-functional teams and domain experts to understand requirements and refine AI solutions.

- Actively contribute to code reviews, technical documentation, and sharing best practices within the team to foster continuous learning.

- Assist in maintaining a high standard of model documentation, from data pipelines to model parameters, training processes, and validation methodologies.

Preferred candidate profile

- Bachelors/Masters in Computer Science, Artificial Intelligence, Machine Learning, or a related field.

- Experience in AI/ML development, with a focus on deep learning, computer vision, and GANs.

- Extensive experience with image segmentation, object detection, and image generation.

- Strong track record of building, optimizing, and deploying large-scale deep learning models.

Employment Type: Full Time, Permanent

Read full job description

Prepare for AI Engineer roles with real interview advice