software engineer

engineering manager

machine learning engineer

LTIMindtree

<div>
 
 
 
 Data Scientist - GENAI
 
 
 
 
 
 
 
 We are looking for a Data Scientist who will support building AI tools for customers. The candidate should be skilled at using large data sets to find opportunities for product and process optimization. The candidate must have a proven ability to drive business results with their data-based insights. The candidate must be comfortable working with a wide range of stakeholders and functional teams.
 
 
 
 
 
 
 
 Primary Skills &ndash; Data Science, Python, AI, ML (Machine Learning) Gen AI &ndash; Generative AI
 
 
 
 
 
 
 
 
 Secondary Skills &ndash;
 
 NLP, LLM, Deep Learning, Cloud (AWS/Cloud)
 
 
 
 
 
 
 
 Responsibilities for Data Scientist:
 
 
 
 
 
 
 <ul>
 <li>
 Work with stakeholders to identify opportunities for leveraging data to drive business solutions.
 </li>
 <li>
 Mine and analyse data from databases to drive optimization and improvement of product development and business strategies.
 </li>
 <li>
 Assess the effectiveness and accuracy of new data sources and data gathering techniques.
 </li>
 <li>
 Develop custom models and algorithms to apply to data sets.
 </li>
 <li>
 Use predictive modelling to increase and optimize customer experiences.
 </li>
 <li>
 Coordinate with different functional teams to implement models and monitor outcomes.
 </li>
 <li>
 Analyse large amounts of information to discover trends and patterns.
 </li>
 <li>
 Build predictive models and machine-learning algorithms.
 </li>
 <li>
 Present information using data visualization techniques .
 </li>
 <li>
 Good to have a knowledge of ML lifecycle and model governance.
 </li>
 </ul>
 
 
 
 
 
 
 Qualifications for Data Scientist
 
 
 
 
 
 
 <ul>
 <li>
 
 
 Looking for someone with 5-8 years of experience manipulating data sets and building statistical models, having bachelor&rsquo;s or master&rsquo;s degree in Statistics, Mathematics, Computer Science or another quantitative field, and is familiar with the following software/tools.
 
 
 </li>
 <li>
 Experience using statistical computer languages (R, Python etc.) to manage data and draw insights from large data sets.
 </li>
 <li>
 Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, XGBoost, KNN, SVM, ANN, etc.).
 </li>
 <li>
 Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
 </li>
 <li>
 Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc.
 </li>
 <li>
 Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc.
 </li>
 <li>
 Experience visualizing/presenting data for stakeholders
 </li>
 <li>
 Experience with Snowflake will be an added advantage
 </li>
 <li>
 Experience in deployment of machine learning models using cloud technologies"
 </li>
 </ul>
 
 
</div>

Data Scientist

Google

<div>
 Note: By applying to this position you will have an opportunity to share your preferred working location from the following:
 
 Bengaluru, Karnataka, India; Gurugram, Haryana, India; Hyderabad, Telangana, India; Mumbai, Maharashtra, India; Pune, Maharashtra, India
 
 .
 
 Minimum qualifications:
 
 
 
 <ul>
 <li>
 Bachelor's degree or equivalent practical experience.
 </li>
 <li>
 Experience working with Unix/Linux environments, distributed systems, machine learning, information retrieval, and TCP/IP.
 </li>
 <li>
 Experience programming in C, C++, Java, or Python.
 
 
 </li>
 </ul>
 
 Preferred qualifications:
 
 
 
 <ul>
 <li>
 Bachelor's or Advanced degree in Computer Science or Computer Engineering, or a related field.
 
 
 </li>
 </ul>
 
 About The Job
 
 
 
 Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google&rsquo;s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
 
 
 As a key member of a small and versatile team, you design, test, deploy and maintain software solutions.
 
 
 Google is an engineering company at heart. We hire people with a broad set of technical skills who are ready to take on some of technology's greatest challenges and make an impact on users around the world. At Google, engineers not only revolutionize search, they routinely work on scalability and storage solutions, large-scale applications and entirely new platforms for developers around the world. From Google Ads to Chrome, Android to YouTube, social to local, Google engineers are changing the world one technological achievement after another.
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Research, conceive, and develop software applications to extend and improve on Google's product offering.
 </li>
 <li>
 Contribute to a wide variety of projects utilizing natural language processing, artificial intelligence, data compression, machine learning, and search technologies.
 </li>
 <li>
 Collaborate on scalability issues involving access to data and information.
 </li>
 <li>
 Solve challenges/problems that you are presented with.
 
 
 
 </li>
 </ul>
 Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form .
</div>

Software Engineer, University Graduate, 2026

Experian

<div>
 
 We are looking for a Data Modeler to help us unlock our vast amounts of data with modelling and advanced analytics, allowing us to make smarter decisions and deliver even better products to our clients. Your primary focus will be in applying data mining techniques, doing statistical analysis, and building high-quality prediction systems and automated scores using machine learning, integrated with our products. You will also support our business teams, pre-sales and analytics to ensure product creation.
 
 
 Suited to someone who has 3 to 4 years' experience core analytics function of a large bank / consulting firm and with experience handling large data volumes using data analysis tools and generating good data insights.
 
 
 
 
 
 
 What you'll do
 
 
 
 
 
 <ul>
 <li>
 Deliver high quality analytical and value-added services for the clients while following timelines as promised to the client.
 </li>
 <li>
 You'll play an important role to Engage Business/Technical Consultants and delivery teams so that there is a shared understanding and agreement as to deliver proposed solution
 </li>
 <li>
 You will Use analysis and customer insights to develop value propositions for customers
 </li>
 </ul>
 
 
 
 
 
 What you'll need to bring to the party
 
 
 
 
 
 <ul>
 <li>
 Understanding of machine learning techniques and algorithms, such as Gradient Boost, KNN, etc.
 </li>
 <li>
 Knowledge of different modelling frameworks like Linear Regression, Logistic Regression, Decision Tree
 </li>
 <li>
 Decent understanding and hands-on of statistical modelling/data analysis tools especially Python, Pyspark or SAS and market trends
 </li>
 <li>
 Applied statistics skills, such as distributions, statistical testing, regression etc.
 </li>
 <li>
 Understanding of decisioning and portfolio management in banking and financial services would be added advantage
 </li>
 <li>
 Understanding of credit bureau would be an added advantage
 </li>
 </ul>
 
 
</div>

Data Modeler II

Deloitte

<div>
 
 
 Your potential, unleashed.
 
 
 
 
 
 India&rsquo;s impact on the global economy has increased at an exponential rate and Deloitte presents an opportunity to unleash and realize your potential amongst cutting edge leaders, and organizations shaping the future of the region, and indeed, the world beyond.
 
 
 
 
 At Deloitte, your whole self to work, every day. Combine that with our drive to propel with purpose and you have the perfect playground to collaborate, innovate, grow, and make an impact that matters.
 
 
 
 
 
 The team
 
 
 
 
 
 The Information Technology department is responsible for building products and platforms for Deloitte India that focuses on providing extraordinary customer experience by putting design thinking with trailblazing technology in the center of what they do. The diverse team consists of subject matter experts, technology specialists, quality engineers, user experience researchers &amp; designers, data scientists and product managers.
 
 
 
 
 
 
 Key Responsibilities:
 
 
 
 
 
 
 1.
 
 NLP Model Development
 
 : Design, develop, and implement state-of-the-art NLP algorithms and models to extract insights and patterns from large volumes of textual data. Leverage machine learning and deep learning techniques to tackle NLP tasks such as text classification, entity extraction, and document summarization.
 
 
 
 
 2.
 
 Data Preprocessing and Feature Engineering
 
 : Preprocess and clean textual data to prepare it for analysis and modeling. Perform feature engineering to extract relevant features and representations from raw text, including word embeddings, n-grams, and syntactic features.
 
 
 
 
 
 3.
 
 Model Evaluation and Validation
 
 : Evaluate the performance of NLP models using appropriate metrics and statistical techniques. Conduct rigorous testing and validation to ensure the accuracy, robustness, and generalization of NLP models across different datasets and domains.
 
 
 
 
 
 4.
 
 NLP Integration
 
 : Collaborate with cross-functional teams, including software engineers and product managers, to integrate NLP solutions into production systems and applications. Ensure seamless interoperability and performance optimization of NLP components within larger AI systems.
 
 
 
 
 
 5.
 
 Research and Innovation
 
 : Stay up-to-date with the latest research in NLP and Gen AI, and apply cutting-edge methodologies to real-world problems. Explore new methodologies, tools, and approaches to improve the effectiveness and efficiency of NLP solutions. Contribute to research publications and thought leadership in the field of NLP.
 
 
 
 
 
 6.
 
 Data Analysis and Visualization
 
 : Analyze and interpret results from NLP models to extract meaningful insights and actionable recommendations. Visualize findings using appropriate techniques and tools to communicate complex information effectively to stakeholders.
 
 
 
 
 
 7.
 
 Documentation and Reporting
 
 : Document methodologies, findings, and insights from NLP projects in clear and concise reports. Communicate technical concepts and results to both technical and non-technical audiences, including management and business stakeholders.
 
 
 
 
 
 
 Qualifications:
 
 
 
 
 
 
 
 &bull;Master's or Ph.D. degree in Computer Science, Engineering, Mathematics, Statistics, or a related field.
 
 
 
 
 
 &bull;Minimum of 5+ years of proven experience as a Data Scientist with a focus on NLP and 2 years on Gen AI, preferably in industry or research settings.
 
 
 
 
 
 &bull;Strong knowledge of NLP techniques and algorithms, including text preprocessing, feature extraction, and supervised and unsupervised learning methods.
 
 
 
 
 
 &bull;Proficiency in programming languages such as Python or R, and libraries such as NLTK, spaCy, scikit-learn, and TensorFlow/PyTorch for NLP.
 
 
 
 
 
 &bull;Familiarity with data visualization tools such as Matplotlib, Seaborn, or Plotly.
 
 
 
 
 
 &bull;Experience with containerization and orchestration technologies such as Docker and Kubernetes.
 
 
 
 
 
 &bull;Basic understanding of system design and ML-Ops practices.
 
 
 
 
 
 &bull;Excellent problem-solving skills and analytical thinking.
 
 
 
 
 
 &bull;Strong communication and collaboration skills, with the ability to work effectively in cross-functional teams.
 
 
 
 
 
 &bull;Proven ability to manage multiple projects simultaneously and meet deadlines in a fast-paced environment.
 
 
 
 
 
 
 Preferred Qualifications:
 
 
 
 
 
 
 
 &bull;Experience with deep learning architectures for NLP, such as recurrent neural networks (RNNs), convolutional neural networks (CNNs), and transformer models (e.g., BERT, GPT).
 
 
 
 
 
 &bull;Knowledge of domain-specific NLP tasks and applications, such as chatbots, document understanding, or information extraction.
 
 
 
 
 
 &bull;Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.
 
 
 
 
 
 How you&rsquo;ll grow
 
 
 
 
 
 
 
 Connect for impact
 
 
 
 
 
 
 Our exceptional team of professionals across the globe are solving some of the world&rsquo;s most complex business problems, as well as directly supporting our communities, the planet, and each other. Know more in our Global Impact Report and our India Impact Report.
 
 
 
 
 
 
 Empower to lead
 
 
 
 
 
 
 You can be a leader irrespective of your career level. Our colleagues are characterised by their ability to inspire, support, and provide opportunities for people to deliver their best and grow both as professionals and human beings. Know more about Deloitte and our One Young World partnership.
 
 
 
 
 
 
 Inclusion for all
 
 
 
 
 
 
 At Deloitte, people are valued and respected for who they are and are trusted to add value to their clients, teams and communities in a way that reflects their own unique capabilities. Know more about everyday steps that you can take to be more inclusive. At Deloitte, we believe in the unique skills, attitude and potential each and every one of us brings to the table to make an impact that matters.
 
 
 
 
 
 
 Drive your career
 
 
 
 
 
 
 At Deloitte, you are encouraged to take ownership of your career. We recognise there is no one size fits all career path, and global, cross-business mobility and up / re-skilling are all within the range of possibilities to shape a unique and fulfilling career. Know more about Life at Deloitte.
 
 
 
 
 
 Everyone&rsquo;s welcome&hellip; entrust your happiness to us
 
 
 
 
 
 Our workspaces and initiatives are geared towards your 360-degree happiness. This includes specific needs you may have in terms of accessibility, flexibility, safety and security, and caregiving. Here&rsquo;s a glimpse of things that are in store for you.
 
 
 
 
 
 Interview tips
 
 
 
 
 
 We want job seekers exploring opportunities at Deloitte to feel prepared, confident and comfortable. To help you with your interview, we suggest that you do your research, know some background about the organisation and the business area you&rsquo;re applying to. Check out recruiting tips from Deloitte professionals.
 
</div>

Perfios

<div>
 
 
 What your average day would look like:
 
 
 
 ● Collaborate with product and engineering teams to understand requirements and devise possible solutions.
 
 
 ● Explore existing research papers, ideas and codebases that can be leveraged in current tasks.
 
 
 ● Search for open source datasets and/or design synthetic data pipelines (including data augmentation).
 
 
 ● Devise and implement experiments using DL/ML models.
 
 
 ● Evaluate the experiments to find failure patterns and come up with improvements in data/model architecture/loss function etc.
 
 
 ● Communicate results and ideas to key stakeholders.
 
 
 ● Optimize the models for production and collaborate with software engineers for deployment.
 
 
 
 Must have skills:
 
 
 
 ● Hands-on experience in dealing with image data and CNN based architectures
 
 
 ● Should have worked on deep learning frameworks (like pytorch, tensorflow, keras etc.)
 
 
 ● Proficient in Python and packages like Numpy, Pandas, OpenCV
 
 
 ● Good understanding of data structures and algorithms along with OOPS, Git, SDLC
 
 
 ● Mathematical intuition of ML and DL algorithms
 
 
 ● Good understanding of Statistics, Linear Algebra and Calculus
 
 
 ● Should be able to perform thorough model evaluation by creating hypotheses on the basis of statistical analyses
 
 
 
 Highly desired:
 
 
 
 ● Hands on experience with latest computer vision model architectures and concepts like ViTs, GANs, Diffusion, Vision Language Models
 
 
 ● Knowledge of training and inference optimizations using CUDA, C++, ONNX, TensorRT, OpenVino etc. and profiling of ML pipelines
 
 
 ● Worked on building production level APIs for serving models (Flask, Django, TF Serving)
 
 
 ● Hands-on experience of using MLOps tools.
 
 
 ● Lead and mentor a team of junior data scientists and analysts, providing technical guidance, code reviews, and career development support.
 
 
 ● Oversee the end-to-end delivery of data science projects by coordinating with cross-functional teams and ensuring alignment with business goals.
 
 
 ● Manage a team of data professionals, fostering a collaborative and innovative work environment to drive analytics excellence.
 
 
 ● Act as a technical lead in projects, taking ownership of team deliverables, timelines, and quality assurance of data models and analytics solutions.
 
 
 ● Facilitate regular team meetings, set goals and priorities, and monitor progress to ensure efficient execution of data-driven initiatives.
 
 
 ● Collaborate with product managers, business stakeholders, and engineering teams while managing a high-performing team of data scientists.
 
 
 ● Champion best practices in data science, model development, and deployment while promoting a culture of continuous learning within the team.
 
</div>

Lead Data Scientist

Larsen & Toubro

<div>
 <ul>
 <li>
 Operate the TBM machine with strong emphasis on safety and report to tunnel engineer/immediate supervisor.
 </li>
 <li>
 Follow tunnel engineer/immediate supervisor&rsquo;s instruction
 </li>
 <li>
 Assist M &amp; E team with assembly and disassembly of TBM
 </li>
 <li>
 All aspects of TBM operation including maintenance of line and grade of the tunnel while steering the TBM, as well as operation of the segment erector and annular grouting systems
 </li>
 <li>
 Involved in proper operations of TBM
 </li>
 <li>
 Checking mining parameters and operation of TBM.
 </li>
 <li>
 Maintaining shift reports, consumption reports for tunneling.
 </li>
 <li>
 All aspects of TBM operation including maintenance of line and grade of the tunnel while steering the TBM, as well as operation of the segment erector and annular grouting systems
 </li>
 <li>
 Involved in proper operations of TBM
 </li>
 <li>
 Checking mining parameters and operation of TBM.
 </li>
 </ul>
</div>

TBM Operator

BNP Paribas

<div>
 
 About BNP Paribas Group
 
 
 
 
 BNP Paribas is a top-ranking bank in Europe with an international profile. It operates in 71 countries and has almost 199 000 employees
 
 . The Group ranks highly in its three core areas of activity: Domestic Markets and International Financial Services (whose retail banking networks and financial services are grouped together under Retail Banking &amp; Services) and Corporate &amp; Institutional Banking, centred on corporate and institutional clients. The Group helps all of its clients (retail, associations, businesses, SMEs, large corporates and institutional) to implement their projects by providing them with services in financing, investment, savings and protection. In its Corporate &amp; Institutional Banking and International Financial Services activities, BNP Paribas enjoys leading positions in Europe, a strong presence in the Americas and has a solid and fast-growing network in the Asia/Pacific region.
 
 
 
 About BNP Paribas India Solutions
 
 
 
 Established in 2005, BNP Paribas India Solutions is a wholly owned subsidiary of BNP Paribas SA, a leading bank in Europe with an international reach. With delivery centers located in Bengaluru, Chennai and Mumbai, we are a 24x7 global delivery center. India Solutions services three business lines: Corporate and Institutional Banking, Investment Solutions and Retail Banking for BNP Paribas across the Group. Driving innovation and growth, we are harnessing the potential of over 6000 employees, to provide support and develop best-in-class solutions.
 
 
 
 About Business Line/Function
 
 
 
 GM Data &amp; AI Lab leverages the power of Machine Learning and Deep learning to drive innovation in various business lines. Our primary goal is to harness the potential of vast amounts of structured and unstructured data to improve our services and provide value. Today we are a team of around 40+ Data Scientists based in Paris, London, Frankfurt, Lisbon, New York, Singapore and Mumbai.
 
 
 
 Job Title
 
 
 
 Data Scientist (Quant Research)
 
 
 
 Date
 
 
 
 Department:
 
 
 Front Office Support
 
 
 Location:
 
 
 Mumbai
 
 
 
 Business Line / Function
 
 
 
 Global Markets &ndash; Data &amp; AI Lab
 
 
 
 Reports To
 
 
 
 (Direct)
 
 
 
 Grade
 
 
 
 (if applicable)
 
 
 (Functional)
 
 
 
 Number Of Direct Reports
 
 
 
 NA
 
 
 
 Directorship / Registration
 
 
 
 NA
 
 
 Position Purpose
 
 
 Your work will center on designing and deploying AI solutions for time series forecasting, financial modeling, anomaly detection and other Quant related usecases. We use AI to discover patterns, classify information, and predict likelihoods. Our team works on building, refining, testing, and deploying these models to support various business use cases, ultimately driving business value and innovation.
 
 
 As a Data Scientist on our team, you can expect to work on challenging projects, collaborate with stakeholders to identify business problems, and have the opportunity to learn and grow with our team. A typical day may involve working on model development, meeting with stakeholders to discuss project requirements/updates, and brainstorming/debugging with colleagues on various technical aspects.
 
 
 At the Lab, we're passionate about staying at the forefront of AI research, bridging the gap between research &amp; industry to drive innovation and to make a real impact on our businesses.
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Develop and maintain AI models on time series &amp; financial date for predictive modelling, including data collection, analysis, feature engineering, model development, evaluation, backtesting and monitoring.
 </li>
 <li>
 Identify areas for model improvement through independent research and analysis, and develop recommendations for updates and enhancements.
 </li>
 <li>
 Working with expert colleagues, Quant and business representatives to examine the results and keep models grounded in reality.
 </li>
 <li>
 Documenting each step of the development and informing decision makers by presenting them options and results.
 </li>
 <li>
 Ensure the integrity and security of data.
 </li>
 <li>
 Provide support for production models delivered by the Mumbai team but potentially as well for other models to any of the Asian/EU/US time zones.
 
 
 </li>
 </ul>
 Technical &amp; Behavioral Competencies
 
 
 <ul>
 <li>
 Bachelor&rsquo;s or Master&rsquo;s degree in a numeric subject with understanding of economics and markets (eg.: Economics with a speciality in Econometrics, Finance, Computer Science, Applied Maths, Engineering, Physics)
 </li>
 <li>
 Knowledge of key concepts in Statistics and Mathematics such as Statistical methods for Machine learning, Probability Theory and Linear Algebra.
 </li>
 <li>
 Knowledge of Monte Carlo Simulations, Bayesian modelling &amp; Causal Inference.
 </li>
 <li>
 Experience with Machine Learning &amp; Deep Learning concepts including data representations, neural network architectures, custom loss functions.
 </li>
 <li>
 Proven track record of building AI models on time-series &amp; financial data.
 </li>
 <li>
 Programming skills in Python and knowledge of common numerical and machine-learning packages (like NumPy, scikit-learn, pandas, PyTorch, PyMC, statsmodels).
 </li>
 <li>
 Ability to write clear and concise code in python.
 </li>
 <li>
 Intellectually curious and willing to learn challenging concepts daily.
 
 
 </li>
 </ul>
 
 Skills Referential
 
 
 
 Behavioural Skills:
 
 
 Ability to collaborate / Teamwork
 
 
 Critical thinking
 
 
 Communication skills - oral &amp; written
 
 
 Attention to detail / rigor
 
 
 
 Transversal Skills
 
 
 
 Analytical Ability
 
 
 
 Education Level
 
 
 
 Bachelor Degree or equivalent
 
 
 Experience Level
 
 
 At least 2 years
</div>

Data Scientist (Quant Research) - GM Data & AI Lab

Explore 70+ Machine learning engineer in Mumbai this December. Find roles across top companies and apply now to boost your career.

70 machine learning engineer jobs IN Mumbai

Data Scientist

Software Engineer, University Graduate, 2026

Data Modeler II

Data Scientist

Lead Data Scientist

TBM Operator

Data Scientist (Quant Research) - GM Data & AI Lab