156 Linear Algebra Jobs - Page 7

Bachelors or Masters degree in Computer Science, AIML/Data Science, Statistics or a related field only. Preferred Institution: NIT (Any) Responsibilities: Architect and deploy scalable Large language models (LLM) and transformer-based architectures. Implement MLOps/LLMOps best practices for CI/CD, automated model retraining, and lifecycle management. Develop advanced AI RAG applications, fine-tune models with PEFT/LoRA, RLHF. Productionize RAG pipelines: embedding strategy, vector-DB design (Weaviate/Pinecone/Chroma). Hybrid search, evaluations and guardrails. Optimize AI/ML pipelines for distributed computing, leveraging cloud platforms and accelerators (GPUs/TPUs). Optimize inference: quantization (INT4/8), speculative decoding, TensorRT-LLM/vLLM, or Ray Serve to reduce token costs. Work closely with data engineers, software developers, and product managers to integrate AI into production systems. Translate complex AI concepts into actionable insights for business stakeholders. Establish governance frameworks for ethical AI, ensuring compliance with industry standards. Required Skills: 5+ years of experience as a AIML Engg. Strong background in statistics, linear algebra, and probability theory Strong proficiency in C++/Python and SQL Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX Build the Agentic LLM applications prototype and launch LLM agents (planner-executor, multi-agent, tool-calling). Experience with LangChain, LlamaIndex, CrewAI, and vector DBs like Weaviate, Pinecone, Qdrant. Experience in Quantization, distillation, GPU kernel tuning. Strong expertise in fine-tuning transformer models, hyperparameter optimization, and reinforcement learning. Proficiency in Azure cloud platform AIML lifecycle CICD - MLOps/LLMOps. Experience in Kubernetes, KubeRay. Familiar with Terraform/Pulumi and observability tools. Lead from the front, responsible for coding, designing, and ensuring best practices & frameworks are adhered by the team. Knowledge of big data processing frameworks (Apache Spark, Hadoop, Data bricks). Create end to end AI systems with responsible AI principles Excellent communication skills to facilitate interactions with stakeholders

About the Team Our Data Science team is the Avengers to Meeshos S.H.I.E.L.D ???. And why not? We are the ones who assemble during the toughest challenges and devise creative solutions, building intelligent systems for millions of our users looking at a thousand different categories of products. Weve barely scratched the surface, and have amazing challenges in charting the future of commerce for Bharat. Our typical day involves dealing with fraud detection, inventory optimisation, and platform vernacularisation. As Lead Data Scientist, you will navigate uncharted territories with us, discovering new paths to creating solutions for our users.?? You will be at the forefront of interesting challenges and solve unique customer problems in an untapped market. But wait theres more to us. Our team is huge on having a well-rounded personal and professional life. When we aren't nose-deep in data, you will most likely find us belting Summer of 69 at the nearest Karaoke bar, or debating who the best Spider-Man is: Maguire, Garfield, or Holland? You tell us ?? About the Role Love deep data? Does innovative-thinking describe you? Then you may be our next Lead Data Scientist. In this role youll be the Dumbledore to our team of wizards - our junior data scientists. You will be responsible for transforming scattered pieces of information into valuable data that can be used to achieve goals effectively. You will extract and mine critical bits of information and drive insightful discussions that result in app innovations. What you will do Own and deliver solutions across multiple charters by formulating well-scoped problem statements and driving them to execution with measurable impact Mentor a team of data scientists (DS2s and DS3s), helping them with project planning, execution, and on-call issue resolution Design and optimize key user journeys (e.g., Reseller Experience, Search, Fraud Systems) by identifying user intents and behavioral patterns from large-scale data Collaborate with machine learning engineers and big data teams to build scalable ML pipelines and improve inference performance Continuously track and improve model performance using state-of-the-art (SOTA) techniques and libraries Lead experimental design for usability improvements and user growth, leveraging statistical rigor Contribute to system-level thinking by enhancing internal tools, frameworks, and libraries to improve team efficiency and code quality Partner with engineering to ensure data reliability, compliance with security/PII guidelines, and integration of models into production systems Proactively explore new areas of opportunity through research, data mining, and academic collaboration, including publishing and attending top-tier conferences Communicate findings, plans, and results clearly with DS, product, and tech stakeholders, and create technical documentation consumable by both DS and engineering teams Conduct research collaborations with premier colleges and universities Attend conferences and publish research papers What you will need A Bachelor's degree in Computer Science, Data Science, or a related field; a Masters is a plus 6--8 years of experience in data science with a strong track record of building and deploying ML solutions at scale Deep understanding of core ML techniques supervised, unsupervised, and semi-supervised learning along with strong foundations in statistics and linear algebra Exposure to deep learning concepts and architectures (e.g., CNNs, RNNs, Transformers) and their practical applications Proficiency in Python and SQL, with experience in building data pipelines and analytical workflows Hands-on experience with large-scale data processing using Apache Spark, Hadoop/Hive, or cloud platforms such as GCP Strong programming fundamentals and experience writing clean, maintainable, and production-ready code Excellent analytical and problem-solving skills the ability to extract actionable insights from messy and high-volume data Solid grasp of statistical testing, hypothesis validation, and common pitfalls in experimental design Experience designing and interpreting A/B tests, including uplift measurement and segmentation Ability to work closely with product and engineering teams to translate business goals into scalable ML or data solutions Bonus points for: Experience with reinforcement learning or sequence modeling techniques Contributions to ML libraries, internal tools, or research publications

About the Team Our Data Science team is the Avengers to Meeshos S.H.I.E.L.D ???. And why not? We are the ones who assemble during the toughest challenges and devise creative solutions, building intelligent systems for millions of our users looking at a thousand different categories of products. Weve barely scratched the surface, and have amazing challenges in charting the future of commerce for Bharat. Our typical day involves dealing with fraud detection, inventory optimisation, and platform vernacularisation. As Data Scientist, you will navigate uncharted territories with us, discovering new paths to creating solutions for our users.?? You will be at the forefront of interesting challenges and solve unique customer problems in an untapped market. But wait theres more to us. Our team is huge on having a well-rounded personal and professional life. When we aren't nose-deep in data, you will most likely find us belting Summer of 69 at the nearest Karaoke bar, or debating who the best Spider-Man is: Maguire, Garfield, or Holland? You tell us ?? About the Role Love deep data? Love discussing solutions instead of problems? Then you could be our next Data Scientist. In a nutshell, your primary responsibility will be enhancing the productivity and utilisation of the generated data. Other things you will do include working closely with the business stakeholders, transforming scattered pieces of information into valuable data and sharing and presenting your valuable insights with peers. What you will do Develop models and run experiments to infer insights from hard data Improve our product usability and identify new growth opportunities Understand reseller preferences to provide them with the most relevant products Designing discount programs to help our resellers sell more Help resellers better recognise end-customer preferences to improve their revenue Use data to identify bottlenecks that will help our suppliers meet their SLA requirements Model seasonal demand to predict key organisational metrics Mentor junior data scientists in the team What you will need Bachelor's/Master's degree in computer science (or similar degrees) 4-7 years of experience as a Data Scientist in a fast-paced organization, preferably B2C Familiarity with Neural Networks, Machine Learning etc. Familiarity with tools like SQL, R, Python, etc. Strong understanding of Statistics and Linear Algebra Strong understanding of hypothesis/model testing and ability to identify common model testing errors Experience designing and running A/B tests and drawing insights from them Proficiency in machine learning algorithms Excellent analytical skills to fetch data from reliable sources to generate accurate insights Experience in tech and product teams is a plus Bonus points for: Experience in working on personalization or other ML problems Familiarity with Big Data tech stacks like Apache Spark, Hadoop, Redshift

Role - Quantum Developer Required Technical Skill Set - Quantum Computing, Optimization, AI/ML Desired Experience Range - 4+ Years Desired Competencies (Technical/Behavioural Competency) Must-Have Strong understanding of quantum mechanics and quantum computing principles Proficiency in python & numerical libraries Experience with quantum frameworks/SDKs (like Qiskit, Pennylane etc.) Immense experience with classical algorithms & optimization techniques Hands-on experience in modelling & solving optimization problems using various solvers Experience with implementing algorithms on NISQ era devices & quantum annealers Strong foundation in linear algebra (advanced), applied mathematics Good-to-Have Familiarity with different cloud-based quantum services like AWS Braket Knowledge in adjacent areas like machine learning, HPC & cryptography Tensorflow & pytorch (for quantum machine learning apps) Responsibility of / Expectations from the Role Design & implement quantum algorithms for specific use cases (on different problem types crypto, optimization, AI/ML, simulation) across different manufacturing domains Develop hybrid quantum-classical solutions using various quantum frameworks/SDK’s like Qiskit, Pennylane, Bracket Deploy & test the solutions on different quantum simulators and hardware from different providers like D-wave, IBM, IonQ etc Design mathematical model for optimization problems (MILP, LP, NLP etc.) Work with the cross functional team to understand the problem requirements and model constraints, objectives & variables Implement the model(s) using solvers like Cplex, Gurobi etc Benchmark the results from quantum solutions against classical methods Explore any new tools/frameworks/products launched in quantum computing space (eg. Cuda-Q)

Bachelors or Masters degree in Computer Science, AIML/Data Science, Statistics or a related field only. Preferred Institution: NIT (Any) Responsibilities: Architect and deploy scalable Large language models (LLM) and transformer-based architectures. Implement MLOps/LLMOps best practices for CI/CD, automated model retraining, and lifecycle management. Develop advanced AI RAG applications, fine-tune models with PEFT/LoRA, RLHF. Productionize RAG pipelines: embedding strategy, vector-DB design (Weaviate/Pinecone/Chroma). Hybrid search, evaluations and guardrails. Optimize AI/ML pipelines for distributed computing, leveraging cloud platforms and accelerators (GPUs/TPUs). Optimize inference: quantization (INT4/8), speculative decoding, TensorRT-LLM/vLLM, or Ray Serve to reduce token costs. Work closely with data engineers, software developers, and product managers to integrate AI into production systems. Translate complex AI concepts into actionable insights for business stakeholders. Establish governance frameworks for ethical AI, ensuring compliance with industry standards. Required Skills: 5+ years of experience as a AIML Engg. Strong background in statistics, linear algebra, and probability theory Strong proficiency in C++/Python and SQL Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX Build the Agentic LLM applications prototype and launch LLM agents (planner-executor, multi-agent, tool-calling). Experience with LangChain, LlamaIndex, CrewAI, and vector DBs like Weaviate, Pinecone, Qdrant. Experience in Quantization, distillation, GPU kernel tuning. Strong expertise in fine-tuning transformer models, hyperparameter optimization, and reinforcement learning. Proficiency in Azure cloud platform AIML lifecycle CICD - MLOps/LLMOps. Experience in Kubernetes, KubeRay. Familiar with Terraform/Pulumi and observability tools. Lead from the front, responsible for coding, designing, and ensuring best practices & frameworks are adhered by the team. Knowledge of big data processing frameworks (Apache Spark, Hadoop, Data bricks). Create end to end AI systems with responsible AI principles Excellent communication skills to facilitate interactions with stakeholders"

Job Title: Assistant Professor Mathematics Department: Science & Humanities (S&H) Institution: CARE College of Engineering, Trichy Position Summary: We are seeking a dynamic and dedicated Assistant Professor in Mathematics to join the S&H Department. The candidate will be responsible for teaching core mathematics subjects to engineering students, contributing to curriculum development, and fostering a strong learning environment through innovative pedagogy and continuous student engagement. Key Responsibilities: Deliver lectures and tutorials in Engineering Mathematics and related subjects to undergraduate students. Prepare and update lesson plans, course materials, and assessments in line with curriculum requirements. Guide students in academic projects and support their mathematical understanding across disciplines. Participate in departmental activities, academic planning, and student mentoring. Contribute to research, publications, and faculty development initiatives. Take part in faculty development programs, workshops, and seminars. Collaborate with colleagues across departments to integrate mathematical tools into engineering subjects. Qualifications: M.Sc. in Mathematics with M.Phil. and NET/SET or Ph.D. Prior teaching experience in engineering