If you are an expert in deep learning, these top 10 deep learning jobs are for you to apply for in March
In this technology-driven era, Artificial intelligence is ruling the world. Its branches like machine learning and deep learning are the field of study that gives computers the capability to learn without being explicitly programmed. As it is evident from the name, it gives the computer that makes it more similar to humans: The ability to learn. Machine learning and deep learning is actively being used today, perhaps in many more places than one would expect. Demand for deep learning professionals is constantly increasing and companies are looking for talented candidates for their deep learning jobs. Since the demand is high and the number of deep learning professionals is less, organizations have no other choice but to give lucrative packages for them. This article features the top 10 best deep learning jobs to apply for in March 2022.
Deep Learning Developer – Techgig
Location: Noida, Uttar Pradesh
Responsibilities:
- As the Senior Deep Learning Developer or Deep Learning Developer, you will utilize the latest tools in Computer Vision, Deep Learning, and Speech Recognition to excel in this emerging industry.
- Be able to train machine learning and deep learning models on a computing cluster to perform visual recognition tasks that would include segmentation, detection, self-supervised depth estimation, and end-to-end control.
- Boost the performance of neural networks with multitask learning, large-scale distributed training, Bayesian deep learning, and uncertainty estimation, multi-sensor fusion, architecture search.
Deep Learning Performance Architect – NVIDIA
Location: New Delhi, Delhi
Responsibilities:
- Analyze the performance of important workloads, tune our current software, and propose improvements for future software
- Work with cross-collaborative teams of deep learning software engineers and GPU architects to innovate across applications like autonomous driving, NLP, computer vision, and recommender systems
- Adapt to the constantly evolving AI industry by being agile and excited to contribute across the codebase, including API design, software architecture, testing, and GPU kernel development
System Software Engineer – Deep Learning – NVIDIA
Location: Pune, Maharashtra
Responsibilities:
- Develop Deep Learning Neural Network Models for Automatic Speech Recognition, Natural Language Processing, and Text to Speech conversion.
- Use TensorFlow, PyTorch, and other Deep Learning Frameworks to develop and test Conversational AI models.
- Implement the full Conversational AI processing pipeline for real-time and embedded systems on NVIDIA GPUs
- Performance evaluation and optimization of the model.
Deep Learning Engineer – Mee 2 Bee Smart Services Pvt. Ltd.
Location: Gurugram, Haryana
Responsibilities:
- International conference papers/Patents, Algorithm design, deep learning development, programming (Python, C/C++)
- The Engineer will be responsible for leading design, development, software implementation for new concept prototypes in the areas of computer vision and deep learning. Based on requirements set by the team, the engineer will help develop new and rapid prototypes for problems related to post-harvest quality assessment in agritech.
Deep Learning Engineer – Gan Studio
Location: Delhi
Responsibilities:
- Owning and solving an end-to-end research problem.
- Being able to re-implement algorithms and match results from Research papers.
- Experience with PyTorch.
Senior Deep Learning R&D Engineer (Compilers) – Intel
Location: Bengaluru, Karnataka
Responsibilities:
- You will be working on cutting edge problems in Deep Learning for Internal AI Accelerator SW Stack
- You will participate in all phases of the software development process: designing, developing, debugging, validation and deployment.
- In this role, you will have the opportunity to develop software for innovative Intel deep learning accelerators
- Deep Learning Compiler – architecture, design, development, and delivery.
- Graph compiler optimizations and kernel compilers.
Senior Deep Learning Engineer – SiteRecon
Location: Noida, Uttar Pradesh
Responsibilities:
- SiteRecon has a mission to be an AI-first company. Your responsibility will be to automate the features we create on our platform. This will include gathering images from multiple sources, overseeing the data creation process, training, and deployment of the model.
AI/ML Engineer – CoreStack
Location: Chennai, Tamil Nadu
Responsibilities:
- Understanding business objectives and formulating the problem as a Machine Learning problem
- Expert level proficiency in Multivariate Time Series Forecasting or Causal Forecasting
- Develop and maintain robust data processing pipelines and reproducible modeling pipelines
- Explore data and communicate insights clearly to non-technical as well as technical audience
- Analyse experimental results, iterate and refine models to create significant business impact
- In-depth understanding of classical statistical forecasting algorithms like ARIMA, ETS, etc. as well as new age algorithms like Prophet.
- Proven experience is handling Time Series Forecasting using standard Regression algorithms like Linear Regression, Gradient Boosted Decision Trees, Random forest, etc.
- Good practical knowledge with Sequence Models in Deep Learning, like LSTMs, Transformers, etc. especially in the context of Time Series Forecasting.
- Proficiency with at least one Deep Learning Framework such as PyTorch, TensorFlow, etc.
Artificial Intelligence Architect & Deep Learning Consultant – Personaliq
Location: Bengaluru, Karnataka
Responsibilities:
- Analyze the performance of various machine learning/DL algorithms on existing/new architectures
- Identify bottlenecks and propose creative solutions to improve them.
- Explore the commonality between deep neural networks and visual computing
- Add new capabilities to data science architectures
- Lead the design of components of our SaaS product.
- Collaborate with other architects to define the overall user experience for the users of the platform.
- Define industry standards for producing large-scale machine learning applications.
Deep Learning Engineer – Nanonets
Location: Bengaluru, Karnataka
Responsibilities:
Candidates would be responsible for building Deep Learning models to solve specific problems. The workflow would look as follows:
- Define Problem Statement (input -> output)
- Preprocess Data
- Build DL model
- Test on different datasets using Transfer Learning
- Parameter Tuning
- Deployment to production
Source: analyticsinsight.net
