5+ Keras Jobs in Chennai | Keras Job openings in Chennai

🎯 Ideal Candidate Profile:

This role requires a seasoned engineer/scientist with a strong academic background from a premier institution and significant hands-on experience in deep learning (specifically image processing) within a hardware or product manufacturing environment.

📋 Must-Have Requirements:

Experience & Education Combinations:

Candidates must meet one of the following criteria:

• Doctorate (PhD) + 2 years of related work experience
• Master's Degree + 5 years of related work experience
• Bachelor's Degree + 7 years of related work experience

Technical Skills:

• Minimum 5 years of hands-on experience in all of the following:
• Python
• Deep Learning (DL)
• Machine Learning (ML)
• Algorithm Development
• Image Processing
• 3.5 to 4 years of strong proficiency with PyTorch OR TensorFlow / Keras.

Industry & Institute:

• Education: Must be from a premier institute (IIT, IISC, IIIT, NIT, BITS) or a recognized regional tier 1 college.
• Industry: Current or past experience in a Product, Semiconductor, or Hardware Manufacturing company is mandatory.
• Preference: Candidates from engineering product companies are strongly preferred.

ℹ️ Additional Role Details:

• Interview Process: 3 technical rounds followed by 1 HR round.
• Work Model: Hybrid (requiring 3 days per week in the office).

Based on the job description you provided, here is a detailed breakdown of the Required Skills and Qualifications for this AI/ML/LLM role, formatted for clarity.

📝 Required Skills and Competencies:

💻 Programming & ML Prototyping:

• Strong Proficiency: Python, Data Structures, and Algorithms.
• Hands-on Experience: NumPy, Pandas, Scikit-learn (for ML prototyping).

🤖 Machine Learning Frameworks:

• Core Concepts: Solid understanding of:
• Supervised/Unsupervised Learning
• Regularization
• Feature Engineering
• Model Selection
• Cross-Validation
• Ensemble Methods: Experience with models like XGBoost and LightGBM.

🧠 Deep Learning Techniques:

• Frameworks: Proficiency with PyTorch OR TensorFlow / Keras.
• Architectures: Knowledge of:
• Convolutional Neural Networks (CNNs)
• Recurrent Neural Networks (RNNs)
• Long Short-Term Memory networks (LSTMs)
• Transformers
• Attention Mechanisms
• Optimization: Familiarity with optimization techniques (e.g., Adam, SGD), Dropout, and Batch Normalization.

💬 LLMs & RAG (Retrieval-Augmented Generation):

• Hugging Face: Experience with the Transformers library (tokenizers, embeddings, model fine-tuning).
• Vector Databases: Familiarity with Milvus, FAISS, Pinecone, or ElasticSearch.
• Advanced Techniques: Proficiency in:
• Prompt Engineering
• Function/Tool Calling
• JSON Schema Outputs

🛠️ Data & Tools:

• Data Management: SQL fundamentals; exposure to data wrangling and pipelines.
• Tools: Experience with Git/GitHub, Jupyter, and basic Docker.

🎓 Minimum Qualifications (Experience & Education Combinations):

Candidates must have experience building AI systems/solutions with Machine Learning, Deep Learning, and LLMs, meeting one of the following criteria:

• Doctorate (Academic) Degree + 2 years of related work experience.
• Master's Level Degree + 5 years of related work experience.
• Bachelor's Level Degree + 7 years of related work experience.

⭐ Preferred Traits and Mindset:

• Academic Foundation: Solid academic background with strong applied ML/DL exposure.
• Curiosity: Eagerness to learn cutting-edge AI and willingness to experiment.
• Communication: Clear communicator who can explain ML/LLM trade-offs simply.
• Ownership: Strong problem-solving and ownership mindset.

JOB DESCRIPTION/PREFERRED QUALIFICATIONS:

REQUIRED SKILLS/COMPETENCIES:

Programming Languages:

• Strong in Python, data structures, and algorithms.
• Hands-on with NumPy, Pandas, Scikit-learn for ML prototyping.

Machine Learning Frameworks:

• Understanding of supervised/unsupervised learning, regularization, feature engineering, model selection, cross-validation, ensemble methods (XGBoost, LightGBM).

Deep Learning Techniques:

• Proficiency with PyTorch or TensorFlow/Keras
• Knowledge of CNNs, RNNs, LSTMs, Transformers, Attention mechanisms.
• Familiarity with optimization (Adam, SGD), dropout, batch norm.

LLMs & RAG:

• Hugging Face Transformers (tokenizers, embeddings, model fine-tuning).
• Vector databases (Milvus, FAISS, Pinecone, ElasticSearch).
• Prompt engineering, function/tool calling, JSON schema outputs.

Data & Tools:

• SQL fundamentals; exposure to data wrangling and pipelines.
• Git/GitHub, Jupyter, basic Docker.

WHAT ARE WE LOOKING FOR?

• Solid academic foundation with strong applied ML/DL exposure.
• Curiosity to learn cutting-edge AI and willingness to experiment.
• Clear communicator who can explain ML/LLM trade-offs simply.
• Strong problem-solving and ownership mindset.

MINIMUM QUALIFICATIONS:

• Doctorate (Academic) Degree and 2 years related work experience; Master's Level Degree and related work experience of 5 years; Bachelor's Level Degree and related work experience of 7 years in building AI systems/solutions with Machine Learning, Deep Learning, and LLMs.

MUST-HAVES:

• Education/qualification:  Preferably from premier Institute like IIT, IISC, IIIT, NIT and BITS. Also regional tier 1 colleges.

• Doctorate (Academic) Degree and 2 years related work experience; or Master's Level Degree and related work experience of 5 years; or Bachelor's Level Degree and related work experience of 7 years

• Min 5 yrs experience in the Mandatory Skills: Python, Deep Learning, Machine Learning, Algorithm Development and Image Processing

• 3.5 to 4 yrs proficiency with PyTorch or TensorFlow/Keras

• Candidates from engineering product companies have higher chances of getting shortlisted (current company or past experience)

QUESTIONNAIRE: 

Do you have at least 5 years of experience with Python, Deep Learning, Machine Learning, Algorithm Development, and Image Processing? Please mention the skills and years of experience:

Do you have experience with PyTorch or TensorFlow / Keras?

• PyTorch
• TensorFlow / Keras
• Both

How many years of experience do you have with PyTorch or TensorFlow / Keras?

• Less than 3 years
• 3 to 3.5 years
• 3.5 to 4 years
• More than 4 years

Is the candidate willing to relocate to Chennai?

• Ready to relocate
• Based in Chennai

What type of company have you worked for in your career?

• Service-based IT company
• Product company
• Semiconductor company
• Hardware manufacturing company
• None of the above

Senior Data Scientist 

We are seeking a Senior Data Scientist Engineer with experience bringing highly scalable enterprise SaaS applications to market. This is a uniquely impactful opportunity to help drive our business forward and directly contribute to long-term growth at Virtana. 

If you thrive in a fast-paced environment, take initiative, embrace proactivity and collaboration, and you’re seeking an environment for continuous learning and improvement, we’d love to hear from you! 

Virtana is a “remote first” work environment so you’ll be able to work from the comfort of your home while collaborating with teammates on a variety of connectivity tools and technologies. 

Work Location- Chennai

Job Type- Hybrid

Role Responsibilities: 

• Research and test machine learning approaches for analyzing large-scale distributed computing applications. 
• Develop production-ready implementations of proposed solutions across different models AI and ML algorithms, including testing on live customer data to improve accuracy, efficacy, and robustness 
• Work closely with other functional teams to integrate implemented systems into the SaaS platform 
• Suggest innovative and creative concepts and ideas that would improve the overall platform  

 Qualifications:    

The ideal candidate must have the following qualifications: 

• 5 + years’ experience in practical implementation and deployment of large customer-facing ML based systems. 
• MS or M Tech (preferred) in applied mathematics/statistics;  CS or Engineering disciplines are acceptable but must have with strong quantitative and applied mathematical skills 
• In-depth working, beyond coursework, familiarity with classical and current ML techniques, both supervised and unsupervised learning techniques and algorithms 
• Implementation experiences and deep knowledge of Classification, Time Series Analysis, Pattern Recognition, Reinforcement Learning, Deep Learning, Dynamic Programming and Optimization 
• Experience in working on modeling graph structures related to spatiotemporal systems 
• Programming skills in Python is a must 
• Experience in developing and deploying on cloud (AWS or Google or Azure) 
• Good verbal and written communication skills 
• Familiarity with well-known ML frameworks such as Pandas, Keras, TensorFlow 

About Virtana:  

Virtana delivers the industry’s only unified software multi-cloud management platform that allows organizations to monitor infrastructure, de-risk cloud migrations, and reduce cloud costs by 25% or more. 

Over 200 Global 2000 enterprise customers, such as AstraZeneca, Dell, Salesforce, Geico, Costco, Nasdaq, and Boeing, have valued Virtana’s software solutions for over a decade. 

Our modular platform for hybrid IT digital operations includes Infrastructure Performance Monitoring and Management (IPM), Artificial Intelligence for IT Operations (AIOps), Cloud Cost Management (Fin Ops), and Workload Placement Readiness Solutions. Virtana is simplifying the complexity of hybrid IT environments with a single cloud-agnostic platform across all the categories listed above. The $30B IT Operations Management (ITOM) Software market is ripe for disruption, and Virtana is uniquely positioned for success. 

Company Profitable Growth and Recognition 

In FY2023 (Fiscal year ending January 2023), Virtana earned: 

—  Best CEO, Best CEO for Women, and Best CEO for Diversity by Comparably 

— Two years in a row YoY Profitable Annual Recurring Revenue (ARR) Growth 

— Two consecutive years of +EBITDA, 78% YoY EBITDA growth, or 20% of Revenue 

— Positive Cash Flow, 171% YoY cash flow growth 

• 3+ years experience in practical implementation and deployment of ML based systems preferred.
• BE/B Tech or M Tech (preferred) in CS/Engineering with strong mathematical/statistical background
• Strong mathematical and analytical skills, especially statistical and ML techniques, with familiarity with different supervised and unsupervised learning algorithms
• Implementation experiences and deep knowledge of Classification, Time Series Analysis, Pattern Recognition, Reinforcement Learning, Deep Learning, Dynamic Programming and Optimisation
• Experience in working on modeling graph structures related to spatiotemporal systems
• Programming skills in Python
• Experience in developing and deploying on cloud (AWS or Google or Azure)
• Good verbal and written communication skills
• Familiarity with well-known ML frameworks such as Pandas, Keras, TensorFlow