Deep Learning Engineer

, 7x faster.

Work with top tier remote

Deep Learning Engineer

, deeply vetted tech talent ready to join build your team or build a project from scratch.

Start your 7 days trial

Schedule an Interview & Hire Developer in 48 Hours

Name required
Email address required
Phone number required
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
Join companies who have trusted
ClanX for their remote engineering needs.


Deep Learning Engineer

who use copilot to code faster

Why Hire 

Deep Learning Engineer

 from ClanX?


Cutting-Edge Expertise | ClanX Deep Learning Engineers are well-versed in the latest advancements in neural networks, ensuring state-of-the-art solutions for complex problems.

Cutting-Edge Expertise | ClanX Deep Learning Engineers are well-versed in the latest advancements in neural networks, ensuring state-of-the-art solutions for complex problems.


Highly Adaptive Skills | These engineers excel at adapting to new technologies and unconventional data, making them ideal for innovative projects.

Highly Adaptive Skills | These engineers excel at adapting to new technologies and unconventional data, making them ideal for innovative projects.


Advanced Analytics | Deploy advanced analytical models that can interpret vast datasets with ease, providing insights that drive strategic decision-making.

Advanced Analytics | Deploy advanced analytical models that can interpret vast datasets with ease, providing insights that drive strategic decision-making.


Efficient Automation | The ability to automate and refine processes using deep learning algorithms translates to increased efficiency and reduced costs.

Efficient Automation | The ability to automate and refine processes using deep learning algorithms translates to increased efficiency and reduced costs.


Solution-Oriented Approach | Deep Learning Engineers from ClanX are adept at crafting bespoke solutions that address specific business challenges effectively.

Solution-Oriented Approach | Deep Learning Engineers from ClanX are adept at crafting bespoke solutions that address specific business challenges effectively.


Robust Problem-Solving | With their strong problem-solving orientation, they can tackle and overcome technical hurdles in project development.

Robust Problem-Solving | With their strong problem-solving orientation, they can tackle and overcome technical hurdles in project development.

Getting started with ClanX

1.  Share your requirements

Tell us more about the problem statement that you are working on and how does your dream team look like. Right from skillset, timezone, experience, you can share everything with us.

2. Get recommendations

Meet highly curated, ready-to-interview builders with verified skills and availability. We do all the heavy lifting so you just need to conduct the final interview round to check for culture fit.

3. Interview and Hire

You conduct the final round with the candidate, based on the feedback either we share more profiles or you hire the talent. Our historical data says, out of 10 builder profiles that we share, 8 get hired.


Deep Learning Engineer

 who has deep expertise in

Meet the go-to tools and tech our skilled

Deep Learning Engineer

use to craft amazing products.

tools | TensorFlow, Keras, PyTorch
databases | MySQL, MongoDB, Hadoop
languages | Python, C++, Java
libraries | NumPy, SciPy, Matplotlib

How Much Does It Cost to Hire Deep Learning Engineers?

With 1-2 years of experience as a deep learning engineer in India, you can expect a competitive Total Cost to Company (CTC) ranging from ₹6-10 lakhs annually. This range is just the beginning, as deep learning engineer salaries can vary based on factors like the company's size, location, and specific skills in deep learning.

As per Glassdoor's data, the base deep learning engineer salary for deep learning engineers in India spans from ₹6L to ₹14L per year, with an average salary of around ₹10L. This indicates a broad spectrum of earning potential in this field, influenced by various factors. 

For those at the higher end of skills and experience, salaries can go up to ₹17L annually, plus additional cash compensations that can significantly increase the total income.

What is a Deep Learning Engineer Salary?

In India, deep learning specialists earn an average yearly compensation of ₹9,50,000. This reflects the high demand for their specialized skills in the tech industry. Additionally, they receive a typical supplementary income of ₹1,50,000, which varies from ₹52,583 to ₹3,00,000, indicating the potential for significant extra earnings based on their project involvement and expertise.

Globally, mid-level deep learning specialists can expect to earn between $110,000 and $140,000 annually, as reported by Glassdoor. This range suggests a substantial reward for developing advanced skills in this niche area.

Senior-level deep learning engineers, especially those with over ten years of experience and sector-specific knowledge, are highly sought after by multinational corporations for director-level roles. 

Their extensive experience not only commands higher salaries but also positions them as key strategic assets in their organizations. This trend underscores the value of continuous learning and specialization in the rapidly evolving field of deep learning.

Is Deep Learning Engineer Still in Demand?

Due to the burgeoning global economy, the demand for professionals skilled in artificial intelligence technologies is on the rise. Notably, forecasts suggest that the market for deep learning engineers could grow by up to 50% by 2024. This growth rate is impressively double that of other IT roles, highlighting the significance of AI in modern technology landscapes.

Hire Deep Learning Engineers

Within the wide and quickly developing field of artificial intelligence, there is a subset of experts that have a special combination of technical expertise and creative imagination. These people are at the vanguard of creating and executing state-of-the-art machine learning algorithms, which power everything from voice recognition software to autonomous robotics. They are referred to as deep learning engineers.

An exceptional attention to detail and a resolute commitment to finding new solutions to challenging issues are essential qualities for deep learning specialists. Their work demands not only a creative approach to building models that can learn from massive amounts of data, but also a command of the mathematical foundations of deep learning. 

Fundamentally, the job of a deep learning engineer involves pushing the limits of artificial intelligence and contributing to the creation of a world that is more intelligent, productive, and connected than it has ever been. However, what precisely does a deep learning engineer do, and what abilities does a successful candidate need to possess? Let's investigate. 

What is Deep Learning?

Artificial neural networks that are inspired by the composition and operations of the human brain are the focus of the machine learning field known as "Deep Learning." It is a hybrid of artificial intelligence (AI) and machine learning that simulates how people learn. Deep learning, predictive modelling, and statistics are all included in data science. 

Deep learning is very useful for deep learning engineers because it makes the process of collecting, analysing, and interpreting large amounts of data faster and easier. Deep learning can be thought of as an automated predictive analytics technique in its most basic form. 

Deep learning algorithms are structured with layers of increasing complexity and abstraction, in contrast to traditional machine learning algorithms.

Deep learning computers analyse data in a way that is comparable to how people come to conclusions. It should be mentioned that both supervised and unsupervised learning can lead to this. 

Artificial neural networks (ANNs), a layered framework of algorithms, are used in deep learning applications to achieve this. With a design modelled after the organic neural network of the human brain, such an ANN may learn far more effectively than standard machine learning models.

What Does a Deep Learning Engineer Do?

Modelling, deployment, and data engineering are all done by deep learning experts. This comprises:

  • Subtasks of data engineering include specifying needs for data, gathering, labelling, examining, cleaning, enhancing, and transferring data.
  • Modelling subtasks, including reviewing research papers, creating assessment metrics, looking for hyperparameters, and training deep learning models.
  • Subtasks related to deployment, such transforming prototyped code into production code, establishing a cloud environment for model deployment, or enhancing response times while conserving bandwidth.

What are Deep Learning Engineer Skills?

Soft skills are just as crucial as technical expertise in machine learning roles. Even as a machine learning expert, your ability to excel in teamwork, effective communication, and time management is key. 

For Deep learning (DL) engineers, a dedication to continuous learning is vital. The fast-paced evolution of data science, machine learning, deep learning, and artificial intelligence means that staying current requires a commitment to ongoing education.

The importance of these non-technical skills cannot be overstated. They enable DL Engineers to collaborate effectively, articulate complex concepts clearly, and manage projects efficiently. 

Additionally, the ever-changing landscape of AI and related fields demands that professionals remain adaptable and open to new knowledge. This blend of soft skills and a learning mindset is essential for navigating the dynamic challenges and advancements in the AI sector.

What are the Technical Deep Learning Engineer Skills?

The Technical skills Needed to Become a deep learning experts are: 

  • Data structures, computer architecture, and software engineering techniques—including the ability to design algorithms for sorting, optimising, and searching—are some of the most important computer science concepts that Deep Learning Engineers need to understand. A DL Engineer should be knowledgeable in software engineering best practices, especially those pertaining to system design, version control, testing, and requirements analysis, as software is their usual output.
  • Data proficiency - A DL Engineer must possess many of the same abilities as a Data Scientist, including data modelling, technical proficiency with Python and Java, and the capacity to evaluate models and prediction algorithms. Additionally helpful would be an understanding of statistics and probability. 
  • Front-end and user interface technologies - When your machine learning solution is ready, present it to others via charts or visualisations, as the person you are speaking with might not be familiar with these techniques and would rather have a workable solution. Thus, being familiar with UI technologies like as Django, Flask, and JavaScript (if needed) can aid in this development process. You will design a frontend for your Machine Learning code, which will serve as the backend.
  • Cloud computing- The amount of data that can be managed locally on a server is increasing at an exponential rate due to technological advancements, which makes cloud technologies necessary. These solutions offer first-rate services that include everything from creating models to preparing data.

Other Frequently Asked Questions (FAQs)

1. How much does it cost to hire a deep learning engineer?

A deep learning engineer in India with 1-2 years of experience can earn ₹6-10L per year, depending on company, location, and skills. Glassdoor reports an average deep learning experts salary of ₹10L, with a maximum of ₹17L plus bonuses. This field offers great opportunities for those who keep learning and growing.

2. Are deep learning engineers in demand?

AI technologies, especially deep learning, are in high demand in the global economy. The market for deep learning engineers could grow 50% by 2024, twice as fast as other IT roles. AI enables innovative solutions across industries, improving efficiency and problem-solving. AI and deep learning offer a rewarding career path with security and growth.

3. Does deep learning have a future?

In the years ahead, we expect deep learning models to advance rapidly, paving the way for innovative applications. These advancements aim to automate tasks that currently require manual effort. One key trend in deep learning is its role in boosting and broadening business operations through networked systems.

Experience ClanX

ClanX is currently in Early Access mode with limited access.

Request Access

Table of Contents


Experience ClanX

ClanX is currently in Early Access mode with limited access.

Request Access


Deep Learning Engineer

who are the best

When it comes to hiring the top

Deep Learning Engineer

, ClanX is the top company in the technology industry that has its own proprietary vetting process which is AI powered.

Deep Learning Consultant | Specialized in evaluating business needs and determining how deep learning technology can resolve specific issues, increasing ROI through tailored AI strategies.

Full-stack Deep Learning Engineer | Capable of handling both the backend and frontend of AI projects, perfect for end-to-end deep learning application development.

Deep Learning for Cloud Computing | Proficient in designing and deploying scalable deep learning models on the cloud, optimizing for performance and cost-efficiency.

Deep Learning Microservices Developer | Expert in building and integrating microservices with deep learning capabilities to enhance modularity and speed of delivery in large applications.

Play Pause
Top-tier tech talent for Growth

Hire elite software engineers, designers and product managers within 48 hours.

Match Rate
ClanX is a true partner. The app was very successful, and our entire company was eventually acquired.
Jayson Dmello
Head of Product, The Girl Tribe
Play Pause
ClanX not only found us the best talent, but also helped us scale up and down as required. Brilliant solution!
Nikunj Ladani
Design Head, GoodWorker

Still Curious? These might help...

What types of projects can Deep Learning Engineers from ClanX handle? | They are capable of taking on a range of projects, from developing intelligent recommendation systems to creating sophisticated image and speech recognition software.

How can a Deep Learning Engineer improve my existing product? | By integrating deep learning models, they can enhance product features such as personalized user experiences, predictive analytics, and autonomous functionalities.

What industries benefit from hiring ClanX's Deep Learning Engineers? | Diverse sectors including healthcare, finance, autonomous vehicles, and e-commerce can reap the benefits of deep learning technology.

Is deep learning applicable to small-scale businesses or startups? | Yes, Deep Learning Engineers can tailor solutions to scale, bringing the power of AI to even the most niche products and services.

What is the typical experience level of a ClanX Deep Learning Engineer? | They are seasoned professionals with extensive backgrounds in AI research and development across various industries.

Can deep learning be integrated into mobile applications? | Absolutely, deep learning can be used for real-time data processing and enhanced user interactions in mobile apps.

What kind of data is needed to start a deep learning project? | Collaborating with ClanX's engineers, they can work with structured, unstructured, or semi-structured data to develop the solution your business requires.

How do Deep Learning Engineers at ClanX stay current with industry advancements? | They regularly engage in continuous learning and professional development to apply the latest techniques and methodologies in their projects.


Deep Learning Engineer

in 48 hours

The ClanX Universe

We have these A+ folks on our talent network

Machine Learning Engineer

Data Engineer

Natural Language Processing Engineer

Computer Vision Engineer

Algorithm Engineer

Robotics Engineer

Deep Learning Engineer

AI Software Developer

AI Hardware Specialist

Research Engineer (AI/ML)

Autonomous Systems Engineer

AI Application Engineer

Machine Learning Infrastructure Engineer

Speech Recognition Engineer

AI Security Engineer

Reinforcement Learning Engineer

AI Research Engineer

Machine Learning Operations (MLOps) Engineer

Machine Intelligence Engineer

Predictive Modeller

Quantitative Machine Learning Engineer

AI Product Engineer

Machine Learning Systems Designer

Edge ML Engineer

Generative Model Engineer

Machine Learning Platform Engineer

Machine Learning DevOps Engineer

AI Optimization Engineer

Conversational AI Engineer

Applied Machine Learning Engineer

AI Solutions Engineer

AI/ML Advisory Engineer

Bioinformatics Engineer

AI Algorithm Optimization Engineer

Language Model Engineer

AI Implementation Engineer

Synthetic Data Engineer

Perception Systems Engineer

AI Research Programmer

Deep Learning Platform Engineer

AI System Validation Engineer

AI/ML Toolchain Engineer

Machine Learning Modeler

AI Innovation Engineer

AI Integration Engineer

AI/ML Test Engineer

AI Software Performance Engineer

AI Data Strategy Engineer

Recommender Systems Engineer

AI Policy Engineer

Metaverse Developer

Backend Engineer

Frontend Engineer

Full Stack Engineer

DevOps Engineer

Software Architect

Mobile Developer (Android)

Mobile Developer (iOS)

Flutter Developer

Embedded Systems Engineer

Site Reliability Engineer (SRE)

Security Engineer

Database Engineer

Systems Engineer

Smart Contract Developer

Network Engineer

UI/UX Developer

Quality Assurance (QA) Engineer

Game Developer

Graphics Engineer

Data Warehouse Engineer

Technical Lead

Scrum Master

Release Engineer

Application Engineer

Infrastructure Engineer

Performance Engineer

Hardware Engineer

React Developers

Test Automation Engineer

Firmware Engineer

Solutions Engineer

Support Engineer

Integration Engineer

Tooling Engineer

Platform Engineer

Data Privacy Engineer

Sales Engineer

Customer Success Engineer

Product Engineer

Compliance Engineer

Accessibility Engineer

Operations Engineer

Video Game Engineer

Virtual Reality (VR) Engineer

Augmented Reality (AR) Engineer

Blockchain Engineer

Cryptography Engineer

Localization Engineer

System Administrator

Network Administrator

User Interface (UI) Engineer

User Experience (UX) Engineer

Golang Developer

Internet of Things (IoT) Engineer

Cloud Infrastructure Engineer

Site Reliability Engineer (SRE)

Automation Architect

DevOps Toolchain Engineer

Security Operations (SecOps) Engineer

Release Manager

Platform Engineer

CI/CD  Engineer

DevOps Consultant

Kubernetes Engineer

Infrastructure as Code (IaC) Developer

DevOps Dashboard Engineer

Observability Engineer

Systems Orchestration Engineer

DevSecOps Engineer

Infrastructure Automation Engineer

Cloud Optimization Engineer

Continuous Delivery Engineer

DevOps Metrics and Analytics Engineer

Production Engineer

Deployment Automation Engineer

Operations Automation Developer

Cloud Security Engineer

Configuration Management Specialist

DevOps Evangelist

Site Operations Engineer

Cloud Systems Engineer

DevOps Compliance Officer

Scalability Engineer

Edge Computing Specialist

AI Product Manager

Technical Product Manager

Data Product Manager

Platform Product Manager

Product Owner (Agile/Scrum)

User Experience Product Manager

Growth Product Manager

Cloud Product Manager

Security Product Manager

Product Compliance Manager

Digital Product Manager

Product Analytics Manager

E-commerce Product Manager

IoT Product Manager

AR/VR Product Manager

Mobile Product Manager

Enterprise Software Product Manager

Customer Success Product Manager

Innovation Product Manager

Sustainability Product Manager

Edge Computing Product Manager

Blockchain Product Manager

DevOps Product Manager

AI Ethics Product Manager

FinTech Product Manager

HealthTech Product Manager

EdTech Product Manager

Biotech Product Manager

Gaming Product Manager

Content Product Manager

Social Media Product Manager

Product Operations Manager

Technical Product Owner

Product Strategy Manager

Internationalisation Product Manager

Accessibility Product Manager

Infrastructure Product Manager

AI/ML Product Manager

Cybersecurity Product Manager

Data Privacy Product Manager

Cloud Services Product Manager

UX/UI Product Manager

Compliance and Regulations Product Manager

Product Quality Manager

User Experience (UX) Designer

User Interface (UI) Designer

Interaction Designer

Product Design Strategist

Visual Designer

Information Architect

User Researcher

Service Designer

UX Writer


Accessibility Designer

UX Engineer

Design Operations Manager

Design System Manager

Design Technologist

UX/UI Developer

Experience Design Lead

Industrial Designer (for physical tech products)

Interaction Design Specialist

Digital Product Designer

Motion Designer (for UI animations)

Brand Experience Designer

Design Researcher

Environmental Designer (for hardware)

Human Factors Engineer

Principal Designer

Creative Technologist

Voice User Interface Designer

Augmented Reality Designer

Virtual Reality Designer

3D Modeler

Color and Material Designer

Wearable Technology Designer

Packaging Designer

Design Sprint Facilitator

Chief Technology Officer (CTO)

Chief Information Officer (CIO)

Chief Product Officer (CPO)

Chief Data Officer (CDO)

Chief Innovation Officer (CINO)

Chief Security Officer (CSO)

Vice President of Engineering

Vice President of Product

Director of Engineering

Director of Product Management

Head of Design

Head of User Experience

Head of Research and Development (R&D)

Program Director

Technical Director

Head of AI/ML

Head of Cloud Services

Head of Data Science

Head of Cybersecurity

Head of Infrastructure

Head of Innovation

Head of IT Operations

Head of Technology Strategy

Head of Digital Transformation

Head of DevOps

Head of Software Development

Head of Platform Development

Head of Technical Architecture

Head of Product Innovation

Head of Quality Assurance

Head of Systems Engineering

Head of Mobile Technology

Head of Enterprise Applications

Head of Internet of Things (IoT)

Head of Robotics