Senior Software Developer at Java developer based in Chandigarh · Chandigarh · 2 - 5 years · ₹10L - ₹20L / yr · Posted 7 Nov 2022

- Build applications to solve business problems in healthcare using Machine Learning techniques and software technologies
- Designing and developing machine learning models
- Running machine learning tests and experiments
- Work with the product and operations team to understand the business
requirements
- Create epics and user stories from requirements
- Prioritize the work based on the changing client requirements
Skills and Specifications:
Required Skills
- Experience in coding with Java
- Experience in working with Spring Framework
- Experience with basic API protocols
- Experience with developing, debugging and dev testing
- Decent communication skills
Nice to have
- Experience with distributed storage & Database Systems (SQL or
NoSQL, eg MySQL or MongoDB)
- Experience with production quality management, deployment &
monitoring.
- Experience with Tomcat, Nginx & Linux.
- Experience with Cloud Technologies (AWS, Azure, Oracle Cloud
etc)
- Product understanding skills.

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About the Internship
Nexora Group is looking for passionate and innovative students interested in Artificial Intelligence (AI) and Machine Learning (ML). This internship offers an opportunity to work on real-world AI projects, explore machine learning techniques, and gain hands-on experience with emerging technologies that are transforming industries worldwide.
Interns will collaborate with mentors, work on practical assignments, and develop industry-relevant skills in AI, ML, data-driven decision-making, and intelligent systems.
Key Responsibilities
- Assist in developing and testing Machine Learning models.
- Work on AI-based applications and automation projects.
- Analyze datasets and prepare data for model training.
- Research emerging AI and Machine Learning technologies.
- Evaluate model performance and improve accuracy.
- Create reports and documentation for assigned projects.
- Participate in project discussions, training sessions, and team meetings.
- Support the development of innovative AI-driven solutions.
Required Skills
- Basic knowledge of Python programming.
- Understanding of Artificial Intelligence and Machine Learning concepts.
- Familiarity with data analysis and statistics.
- Knowledge of Machine Learning libraries such as Scikit-learn, TensorFlow, or PyTorch is a plus.
- Strong analytical and problem-solving skills.
- Ability to learn new technologies quickly.
- Good communication and teamwork skills.
Eligibility
- B.Tech, M.Tech, BCA, MCA, B.Sc., M.Sc., or related disciplines.
- Students pursuing Computer Science, Artificial Intelligence, Data Science, Information Technology, Mathematics, or related fields.
- Freshers and recent graduates are encouraged to apply.
What You Will Learn
✅ Artificial Intelligence Fundamentals
✅ Machine Learning Algorithms
✅ Data Preprocessing & Model Training
✅ Generative AI Concepts
✅ Predictive Analytics
✅ AI Project Development
✅ Industry-Oriented Problem Solving
Benefits
✅ Internship Completion Certificate
✅ Letter of Recommendation (Performance-Based)
✅ Hands-on AI & ML Project Experience
✅ Professional Mentorship & Guidance
✅ Resume & LinkedIn Profile Enhancement
✅ Portfolio Development Support
✅ Exposure to Real-World AI Applications
About Nexora Group
Nexora Group is a technology and innovation-driven organization dedicated to building intelligent solutions that leverage Artificial Intelligence, Machine Learning, Data Analytics, and emerging technologies. We are committed to fostering talent by providing aspiring professionals with practical exposure, mentorship, and opportunities to work on real-world projects.
Internship Overview
Nexora Group is looking for enthusiastic and driven AI/ML Interns to join our team. This internship is ideal for students and recent graduates who are passionate about Artificial Intelligence, Machine Learning, Deep Learning, and Generative AI. Interns will gain hands-on experience working on real-world AI projects, developing intelligent models, and solving complex business challenges using data-driven approaches.
Key Responsibilities
- Assist in developing, training, and evaluating Machine Learning models.
- Collect, clean, and preprocess datasets for AI/ML applications.
- Conduct exploratory data analysis and feature engineering.
- Work on Deep Learning, Natural Language Processing (NLP), and Computer Vision projects.
- Research and implement AI algorithms and emerging technologies.
- Support the development of Generative AI and Large Language Model (LLM)-based solutions.
- Optimize model performance and evaluate results using industry-standard metrics.
- Document project workflows, findings, and technical reports.
- Collaborate with cross-functional teams to develop innovative AI solutions.
Required Skills
- Basic understanding of Machine Learning and Artificial Intelligence concepts.
- Knowledge of Python programming.
- Familiarity with libraries such as NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch, or Keras.
- Understanding of data structures, algorithms, and statistics.
- Basic knowledge of Deep Learning, NLP, or Computer Vision concepts.
- Strong analytical and problem-solving skills.
- Good communication and teamwork abilities.
- Willingness to learn and adapt to new technologies.
Preferred Qualifications
- Experience with AI/ML projects, hackathons, or research work.
- Knowledge of Generative AI, Prompt Engineering, and LLMs.
- Familiarity with cloud platforms and AI deployment tools.
- Certifications in AI, Machine Learning, or Data Science are a plus.
- GitHub projects or portfolio showcasing AI/ML work.
Eligibility
- Undergraduate or postgraduate students pursuing Computer Science, Artificial Intelligence, Machine Learning, Data Science, Information Technology, or related fields.
- Recent graduates seeking practical industry experience.
- Candidates with a strong interest in AI innovation and research.
What You'll Gain
- Hands-on experience with real-world AI and Machine Learning projects.
- Mentorship from experienced AI professionals.
- Exposure to cutting-edge AI tools, frameworks, and technologies.
- Internship Completion Certificate.
- Letter of Recommendation based on performance.
- Opportunity for a Pre-Placement Offer (PPO) for outstanding performers.
- Professional networking and career development opportunities.
We are looking for a talented and driven Data Scientist to join our growing Analytics team in India. In this role, you will work at the intersection of advanced machine learning, scalable MLOps infrastructure, and domain-specific healthcare analytics. You will collaborate closely with cross-functional teams to build, deploy, and maintain production-grade ML models that drive real-world impact in clinical trials and healthcare operations.
KEY RESPONSIBILITIES
End-to-End ML Development
• Design, build, and optimize predictive models across the full ML lifecycle—from data ingestion to model serving.
• Conduct rigorous Exploratory Data Analysis (EDA) to surface insights and drive feature engineering decisions.
• Validate model performance using appropriate statistical techniques and domain knowledge.
MLOps & Production Deployment
• Deploy, monitor, and maintain production-grade ML models using Databricks MLFlow endpoints and Unity Catalog.
• Implement CI/CD pipelines for model versioning, experiment tracking, and automated retraining.
• Ensure model reliability, observability, and performance in live production environments.
Language Models & LLM Applications
• Apply transformer-based models (BERT, ClinicalBERT, Trial2Vec) for NLP tasks including classification, NER, and information extraction.
• Build and maintain vector similarity search pipelines for semantic retrieval and recommendation use cases.
• Fine-tune pre-trained models for domain-specific applications in clinical and healthcare contexts.
• Support exploratory work around LLM integration and prompt engineering for internal tooling.
Domain-Driven Analytics
• Apply advanced analytics within complex healthcare and clinical trial datasets—including patient records, trial protocols, and adverse event data.
• Translate ambiguous business problems into structured analytical frameworks with measurable outcomes.
• Partner with domain experts, product managers, and engineering teams to deliver data-driven solutions.
REQUIRED QUALIFICATIONS
Education
• Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Bioinformatics, or a closely related field.
Experience
• 2–4 years of hands-on experience in a data science or machine learning role.
• Demonstrable experience deploying ML models in production environments (not just prototyping).
Technical Skills
• Strong proficiency in Python (pandas, NumPy, scikit-learn, PyTorch / TensorFlow).
• Experience with Databricks, MLFlow (experiment tracking, model registry, endpoints), and Unity Catalog.
• Hands-on experience with BERT-family models and Hugging Face Transformers library.
• Familiarity with vector databases (e.g., FAISS, Pinecone, Weaviate) and embedding-based retrieval.
• Solid understanding of SQL and working with large structured/unstructured datasets.
• Exposure to cloud platforms (AWS / GCP / Azure) and distributed computing frameworks (Spark).
GOOD TO HAVE
• Prior experience with clinical trial data standards (CDISC, CDASH, SDTM) or healthcare ontologies (SNOMED, ICD-10).
• Familiarity with Trial2Vec or similar trial-to-vector embedding approaches.
• Experience with LLM fine-tuning, RAG pipelines, or prompt engineering in a production setting.
• Knowledge of regulatory and compliance considerations in healthcare AI (e.g., FDA guidelines, HIPAA).
• Contributions to open-source ML projects or published research.
THIS ROLE IS NOT FOR YOU IF…
• You have strong SQL/BI skills but limited hands-on ML modelling experience — or you’ve built models only in notebooks without ever deploying them to production.
• Your LLM exposure is limited to API calls and prompt engineering — with no experience fine-tuning models, working with embeddings, or building vector search pipelines.
Job Description:
We are seeking a highly skilled Machine Learning Engineer to join our team. The ideal candidate will have a strong background in Natural Language Processing (NLP), Large Language Models (LLMs), and Python programming.
You will work closely with data scientists, product managers, and data engineers to design, develop, and deploy high-performance AI/ML models and integrate generative AI solutions into existing workflows.
Your responsibilities will include:
- Collaborating with cross-functional teams to design and deliver high-performance AI models, including NLP, computer vision, semantics engines, linguistic analysis, risk management, and time-series prediction models. Integrating generative AI solutions into existing workflow systems.
- Developing and maintaining the ML Operations CI/CD pipeline for seamless deployment and monitoring. Training, tuning, and optimizing AI models and algorithms for enhanced performance.
- Implementing complex real-time data and AI/ML applications to capture knowledge and automate decision-making processes.
- Creating ML/AI models for business teams and establishing metrics to track their accuracy and performance. Overseeing the full lifecycle of algorithm development, from ideation to deployment and monitoring. Evaluating and ranking ML algorithms based on their potential success in solving specific problems.
- Serving as an internal resource for AI/ML needs, providing guidance and insights to stakeholders during strategic discussions.
Required Experience and Skills:
Machine Learning:
- Proficient in generative AI techniques, prompt engineering, and Retrieval-Augmented Generation (RAG) (3+ years).
- Experience with Large Language Models (LLMs) such as OpenAI, Gemini, LLAMA, and other state-of-the-art models (3+ years).
- Expertise in using ML/AI libraries such as Pandas, NumPy, PyTorch, TensorFlow, Keras, BERT, LayoutLM, and traditional ML algorithms (5+ years).
- Experience with distributed ML/AI training libraries/models: Koalas, Horovod, DDP.
Python Programming and Software Engineering:
- Expertise in Pythonic clean coding practices, including the use of decorators, generators, and descriptors (5+ years).
- Strong understanding of software design principles such as DRY, OAOO, YAGNI, KIS, EAFP/LBYL, and defensive programming (2+ years).
- Proficient in software design concepts focusing on cohesion and coupling (2+ years). Knowledge of SOLID principles (2+ years).
Education and Experience:
- Minimum Bachelor's degree or foreign equivalent in Computer Science, Electrical Engineering, or a closely related field.
- At least 5 years of experience as a software engineer and 5 years of ML-related programming.
We are seeking a Senior Data Science & ML Associate with 4+ years of applied ML experience to build and ship models end-to-end from data prep and feature engineering to training, evaluation, and deployment driving measurable business impact.
Key Responsibilities
• Build, train, and evaluate ML and deep-learning models
• Engineer features and prepare data at scale
• Deploy models and monitor production performance
• Partner with stakeholders to frame problems and metrics
• Communicate results and drive decisions
• Iterate on models from business feedback
Mandatory Skills
• 4+ years applied machine learning
• Strong Python (Pandas, NumPy, scikit-learn)
• Classical ML and deep learning (TensorFlow/PyTorch)
• Solid statistics and experiment design
• SQL and data wrangling at scale
• Model deployment / MLOps exposure
Nice to Have: NLP or computer vision; cloud ML (SageMaker, Azure ML)
ML DEVELOPER
Hyperworks Imaging is a cutting-edge technology company based out of Bengaluru, India since 2016. Our team uses the latest advances in deep learning and multi-modal machine learning techniques to solve diverse real world problems. We are rapidly growing, working with multiple companies around the world.
JOB OVERVIEW
We are seeking a talented and results-oriented ML Developer to join our growing team in India. In this role, you will be responsible for developing and implementing new advanced ML algorithms and AI agents for creating AI assistants of the future.
The ideal candidate will work on a complete ML pipeline starting from extraction, transformation and analysis of data to developing novel ML algorithms. The candidate will implement latest research papers and closely work with various stakeholders to ensure data-driven decisions and integrate the solutions into a robust ML pipeline.
RESPONSIBILITIES:
- Create AI agents using Model Context Protocols (MCPs), Claude Code, DsPy etc.
- Develop custom evals for AI agents.
- Build and maintain ML pipelines
- Optimize and evaluate ML models to ensure accuracy and performance.
- Define system requirements and integrate ML algorithms into cloud based workflows.
- Write clean, well-documented, and maintainable code following best practices
REQUIREMENTS:
- 2-3+ years of experience in data science, machine learning, or a similar role.
- Demonstrated expertise with python, PyTorch, and TensorFlow.
- Graduated/Graduating with B.Tech/M.Tech/PhD degrees in Electrical Engg./Electronics Engg./Computer Science/Maths and Computing/Physics
- Has done coursework in Linear Algebra, Probability, Image Processing, Deep Learning and Machine Learning.
- Has demonstrated experience with Model Context Protocols (MCPs), DSPy, AI Agents, MLOps etc
WHO CAN APPLY:
Only those candidates will be considered who,
- have relevant skills and interests
- can commit full time
- Can show prior work and deployed projects
- can start immediately
Please note that we will reach out to ONLY those applicants who satisfy the criteria listed above.
SALARY DETAILS: Commensurate with experience.
JOINING DATE: Immediate
JOB TYPE: Full-time
Sr Engineer – Artificial Intelligence
Job Summary
As an AI Engineer at Emerson, you will be responsible for analysing complex data sets to
identify trends, develop predictive models, and provide actionable insights. You will work closely
with cross-functional teams to understand business needs and deliver data-driven solutions that
enhance decision-making and drive business growth.
In This Role, Your Responsibilities Will Be:
Analyze large, complex data sets using statistical methods and machine learning
techniques to extract meaningful insights.
Develop and implement predictive models and algorithms to solve business problems
and improve processes.
Create visualizations and dashboards to effectively communicate findings and insights to
stakeholders.
Work with data engineers, product managers, and other team members to understand
business requirements and deliver solutions.
Clean and preprocess data to ensure accuracy and completeness for analysis.
Prepare and present reports on data analysis, model performance, and key metrics to
stakeholders and management.
Participate in regular Scrum events such as Sprint Planning, Sprint Review, and Sprint
Retrospective
Stay updated with the latest industry trends and advancements in data science and
machine learning techniques.
For This Role, You Will Need:
Bachelor’s degree in computer science, Data Science, Statistics, or a related field or a
master's degree or higher is preferred.
Total 5-7 years of industry experience
More than 3 years of experience in a data science or analytics role, with a strong track
record of building and deploying models.
Proficiency in programming languages such as Python or R, and experience with data
manipulation libraries (e.g., pandas, NumPy).
Excellent understanding of Agentic Frameworks like Microsoft Agent Framework.
Experience with NLP, NLG, and Large Language Models Open Source as well as Cloud
based models.
Experience with SQL and NoSQL databases such as MongoDB, Cassandra, Vector
databases
Experience with Dockers, Asynchronous Data Orchestrators, environments etc.
Strong analytical and problem-solving skills, with the ability to work with complex data
sets and extract actionable insights.
Excellent verbal and written communication skills, with the ability to present complex
technical information to non-technical stakeholders.
Preferred Qualifications that Set You Apart:
Prior experience in engineering domain would be nice to have
Prior experience in working with teams in Scaled Agile Framework (SAFe) is nice to
have
Possession of relevant certification/s in data science from reputed universities
specializing in AI.
Familiarity with cloud platforms, Microsoft Azure is preferred
Ability to work in a fast-paced environment and manage multiple projects simultaneously.
Strong analytical and troubleshooting skills, with the ability to resolve issues related to
model performance and infrastructure.
We are looking for a talented and driven Data Scientist to join our growing Analytics team in India. In this role, you will work at the intersection of advanced machine learning, scalable MLOps infrastructure, and domain-specific healthcare analytics. You will collaborate closely with cross-functional teams to build, deploy, and maintain production-grade ML models that drive real-world impact in clinical trials and healthcare operations.
KEY RESPONSIBILITIES
End-to-End ML Development
• Design, build, and optimize predictive models across the full ML lifecycle—from data ingestion to model serving.
• Conduct rigorous Exploratory Data Analysis (EDA) to surface insights and drive feature engineering decisions.
• Validate model performance using appropriate statistical techniques and domain knowledge.
MLOps & Production Deployment
• Deploy, monitor, and maintain production-grade ML models using Databricks MLFlow endpoints and Unity Catalog.
• Implement CI/CD pipelines for model versioning, experiment tracking, and automated retraining.
• Ensure model reliability, observability, and performance in live production environments.
Language Models & LLM Applications
• Apply transformer-based models (BERT, ClinicalBERT, Trial2Vec) for NLP tasks including classification, NER, and information extraction.
• Build and maintain vector similarity search pipelines for semantic retrieval and recommendation use cases.
• Fine-tune pre-trained models for domain-specific applications in clinical and healthcare contexts.
• Support exploratory work around LLM integration and prompt engineering for internal tooling.
Domain-Driven Analytics
• Apply advanced analytics within complex healthcare and clinical trial datasets—including patient records, trial protocols, and adverse event data.
• Translate ambiguous business problems into structured analytical frameworks with measurable outcomes.
• Partner with domain experts, product managers, and engineering teams to deliver data-driven solutions.
REQUIRED QUALIFICATIONS
Education
• Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Bioinformatics, or a closely related field.
Experience
• 2–4 years of hands-on experience in a data science or machine learning role.
• Demonstrable experience deploying ML models in production environments (not just prototyping).
Technical Skills
• Strong proficiency in Python (pandas, NumPy, scikit-learn, PyTorch / TensorFlow).
• Experience with Databricks, MLFlow (experiment tracking, model registry, endpoints), and Unity Catalog.
• Hands-on experience with BERT-family models and Hugging Face Transformers library.
• Familiarity with vector databases (e.g., FAISS, Pinecone, Weaviate) and embedding-based retrieval.
• Solid understanding of SQL and working with large structured/unstructured datasets.
• Exposure to cloud platforms (AWS / GCP / Azure) and distributed computing frameworks (Spark).
GOOD TO HAVE
• Prior experience with clinical trial data standards (CDISC, CDASH, SDTM) or healthcare ontologies (SNOMED, ICD-10).
• Familiarity with Trial2Vec or similar trial-to-vector embedding approaches.
• Experience with LLM fine-tuning, RAG pipelines, or prompt engineering in a production setting.
• Knowledge of regulatory and compliance considerations in healthcare AI (e.g., FDA guidelines, HIPAA).
• Contributions to open-source ML projects or published research.
THIS ROLE IS NOT FOR YOU IF…
• You have strong SQL/BI skills but limited hands-on ML modelling experience — or you’ve built models only in notebooks without ever deploying them to production.
• Your LLM exposure is limited to API calls and prompt engineering — with no experience fine-tuning models, working with embeddings, or building vector search pipelines.







