5,434 Computational Linguistics jobs in India
Machine Learning
Posted today
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Overview:
TekWissen Group is a workforce management provider throughout India and many other countries in the world, the Client has proven expertise in ASIC design from Spec to Silicon and software development end to end.
Job Title: Machine Learning
Location: Pune
Job Type: Full Time
Work Type: Onsite
Job Description:
- The CUSTOMER Wireless Connectivity's DSP team is a highly visible team responsible for PHY layer algorithm design, digital verification, and silicon bring-up for next-gen WLAN and narrowband transceivers.
- The team is also involved in development of Machine Learning based algorithms for Wireless Applications
As part of this core team, the contractor would:
- Construct real-life setups to collect training data for ML applications and test performance in cabled and OTA environments
- Develop machine learning algorithms using python/MATLAB from concept to deployment
- Perform model tuning and simulations for performance optimization
- Deploy concepts from ML and Wireless Communication theory to develop cutting edge technology
- Collaborate with design engineers to develop area/power efficient hardware implementations and assist in verification efforts Key
Qualifications:
- 3+ years of professional programming experience in Python/MATLAB for AIML model/M.Tech/M.S/Ph.D in electrical engineering/computer science (specialization in fields related to AIML/wireless/signal processing)
- Strong analytical and problem-solving skills Exposure to machine learning libraries such as Tensorflow/Pytorch etc.
would be preferable:
- Knowledge of wireless communications and signal processing would be a plus
TekWissen Group is an equal opportunity employer supporting workforce diversity.
Machine Learning Engineer
Posted 4 days ago
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**Location:** Hybrid
**Job Type:** Full-time
**About Us:**
Ralliant is at the forefront of leveraging data and AI technologies to drive innovation across Precision Tech Industries. We aim to solve real-world challenges by combining advanced machine learning, cloud computing, and generative AI to deliver cutting-edge solutions. We're looking for a talented and passionate **MLE** to join our dynamic team and help us continue to push the boundaries of AI.
· **Model Deployment & MLOps:**
+ Design, build, and maintain machine learning pipelines, ensuring continuous integration and deployment (CI/CD) of models in production environments.
+ Deploy machine learning models as APIs, microservices, or serverless functions for real-time inference.
+ Manage and scale machine learning workloads using Kubernetes, Docker, and cloud-based infrastructure (AWS, Azure, GCP).
· **Automation & Scripting:**
+ Automate routine tasks across the ML lifecycle (data preprocessing, model training, evaluation, deployment) using Python, Bash, and other scripting tools.
+ Implement automation for end-to-end model management and monitor pipelines for health, performance, and anomalies.
· **Cloud Platforms & Infrastructure:**
+ Utilize cloud platforms (AWS, Azure, GCP) to optimize the scalability, performance, and cost-effectiveness of ML systems.
+ Leverage Infrastructure as Code (IaC) tools like Terraform or CloudFormation to provision and manage cloud resources effectively.
· **Data Pipelines & Integration:**
+ Build and maintain robust data pipelines to streamline data ingestion, preprocessing, and feature engineering.
+ Work with both structured and unstructured data sources and databases (SQL, NoSQL) to feed data into ML models.
· **Monitoring, Logging & Troubleshooting:**
+ Set up monitoring and logging systems to track model performance, detect anomalies, and maintain system health.
+ Diagnose and resolve issues across the machine learning pipeline and deployed models.
· **Collaboration & Communication:**
+ Collaborate closely with data scientists, software engineers, and business stakeholders to ensure machine learning models meet the required business objectives and performance standards.
+ Effectively communicate complex ML concepts and technical details to non-technical stakeholders.
· **GenAI & AI Agents Expertise:**
+ Stay up to date with the latest trends in Generative AI (e.g., GPT models, Diffusion models) and AI agents, and bring this expertise into production environments.
+ Design and deploy advanced GenAI solutions, ensuring they are aligned with business needs and ethical AI principles.
· **Security & Compliance:**
+ Implement robust security measures for machine learning models and ensure compliance with relevant data protection and privacy regulations.
+ Address vulnerabilities, ensuring safe and secure deployment of models in production environments.
· **Optimization & Cost Management:**
+ Optimize machine learning resources (compute, memory, storage) to achieve high performance while minimizing operational costs.
+ Regularly review and improve the efficiency of machine learning workflows.
· **Testing & Validation:**
+ Develop and execute rigorous testing and validation strategies to ensure the reliability, accuracy, and fairness of deployed models.
+ Use automated testing frameworks to continuously validate model performance.
**Required Skills & Qualifications:**
+ **Education** : Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field.
+ **Experience** :
+ Proven experience (3+ years) in machine learning engineering, MLOps, or related fields.
+ Experience with deploying and managing machine learning models in production using tools like Kubernetes, Docker, and CI/CD pipelines.
+ Hands-on experience with cloud platforms (AWS, Azure, GCP) and infrastructure automation tools (Terraform, CloudFormation).
+ Strong coding experience in Python, Bash, or other scripting languages.
+ Expertise in Generative AI models (e.g., GPT, GANs) and their deployment at scale.
+ Experience working with databases (SQL, NoSQL) and building data pipelines.
+ **DevOps & CI/CD** :
+ Knowledge of DevOps tools and practices, including version control (Git), automated testing, and continuous integration/deployment.
+ **AI Agents** : Familiarity with the latest AI agent frameworks and their deployment in real-world applications.
+ **Data Science Concepts** : Solid understanding of GenAI,NLP, Computer Vision, machine learning algorithms, data structures, and model evaluation techniques.
+ **Problem-Solving** : Strong troubleshooting and debugging skills to quickly identify and fix issues within ML pipelines and deployments.
+ **Collaboration & Communication** : Excellent communication skills with the ability to work in a cross-functional team and explain technical concepts to non-technical stakeholders.
**Preferred Qualifications:**
+ Certification in Cloud Technologies (AWS, Azure, GCP) and MLOps platforms.
+ Experience with large-scale ML systems and distributed computing.
+ Understanding of ethical AI practices and AI fairness.
+ Familiarity with cutting-edge AI technologies like reinforcement learning, AI agents, and deep learning.
**Technical Skills:**
+ Proficiency in Python, R, or other relevant programming languages.
+ Strong knowledge of machine learning libraries such as TensorFlow, PyTorch, Scikit-learn, or Keras.
+ Experience with SQL and cloud-native data processing tools (e.g., AWS Redshift, Azure Synapse, Spark).
+ Familiarity with DevOps practices and CI/CD pipelines for ML model deployment.
**Soft Skills:**
+ Strong communication skills with the ability to translate complex technical concepts into business-friendly language.
+ Problem-solving mindset, with the ability to approach challenges creatively and collaborate with diverse teams.
+ Leadership potential or experience mentoring junior team members.
**Preferred Qualifications:**
+ Certification or training in AWS (e.g., AWS Certified Machine Learning), Azure, or other cloud services.
+ Experience working with containerization technologies like Docker and Kubernetes for model deployment.
+ Exposure to the latest trends in AI ethics, explainability, and fairness.
**Company Overview:**
Join a dynamic and innovative team at Ralliant, a leader in producing high-tech measurement instruments and essential sensors. Our brands, including Tektronix, Qualitrol, Sensing Technologies and Pacific Scientific, are at the forefront of technological advancements, providing critical products that drive innovation across various industries. At Ralliant, we are committed to excellence and continuous improvement, delivering top-tier solutions that meet the evolving needs of our Operating Companies
**These are the traits we value:**
+ You are collaborative, proactive, adaptable, and gritty. You excel at facilitating and reconciling inputs across separated geo-located teams. You balance a passion for deep understanding of innovation with the ability to deliver extraordinary results.
+ Ability to Deliver Results: A track record for delivering results with concrete financial and operational objectives as well as the capacity to organize and direct a small team.
+ Entrepreneurial Attitude: A proactive outlook that provides the chutzpah needed to overcome barriers, creatively problem solve, and test conventional thinking.
+ Comfort with Ambiguity: A willingness and aptitude for spending time in and thriving with deep uncertainty and environments where there is no clear "right answer".
+ Passion for Innovation: A demonstrated interest and desire to participate in innovation through personal study, on-the-job initiative, or other endeavors.
+ Positive Outlook: A desire to look past the objections in search of the opportunity.
+ Strong Communication Skills: An ability to explain new concepts clearly and succinctly, able to negotiate and persuade others to your point of view.
+ A need for speed; demonstrated ability to make decisions quickly and to act upon them.
+ Alongside a team of entrepreneurial, high-performing, curious people, you'll deliver breakthrough solutions to drive sustainable growth for Ralliant
**Bonus or Equity**
This position is also eligible for bonus as part of the total compensation package.
**Ralliant Corporation Overview**
Ralliant, originally part of Fortive, now stands as a bold, independent public company driving innovation at the forefront of precision technology. With a global footprint and a legacy of excellence, we empower engineers to bring next-generation breakthroughs to life - faster, smarter, and more reliably. Our high-performance instruments, sensors, and subsystems fuel mission-critical advancements across industries, enabling real-world impact where it matters most. At Ralliant we're building the future, together with those driven to push boundaries, solve complex problems, and leave a lasting mark on the world.
We Are an Equal Opportunity Employer
Ralliant Corporation and all Ralliant Companies are proud to be equal opportunity employers. We value and encourage diversity and solicit applications from all qualified applicants without regard to race, color, national origin, religion, sex, age, marital status, disability, veteran status, sexual orientation, gender identity or expression, or other characteristics protected by law. Ralliant and all Ralliant Companies are also committed to providing reasonable accommodations for applicants with disabilities. Individuals who need a reasonable accommodation because of a disability for any part of the employment application process, please contact us at
**About NewCo**
**Bonus or Equity**
This position is also eligible for bonus as part of the total compensation package.
Machine Learning Expert
Posted today
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Role Description
This is a contract role for a Machine Learning Expert. The Machine Learning Expert will be responsible for developing and implementing machine learning models, conducting research, and analyzing data sets. Day-to-day tasks include designing algorithms, evaluating model performance, and collaborating with cross-functional teams to deploy solutions.
Qualifications
- Proficient in Machine Learning, Deep Learning, and developing algorithms
- Strong background in Computer Science and Statistics
- Ability to conduct research and analyze data sets
- Experience with model performance evaluation and deployment
- Excellent problem-solving and analytical skills
- Advanced degree in Computer Science, Engineering, Mathematics, or a related field
- Solid knowledge of transformers development and understanding of the whole transformer infrastructure.
- Should have experience or won't be entertained.
Machine Learning Specialist
Posted today
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Role Description
We are seeking a highly skilled Machine Learning Engineer to contribute to diverse healthcare and in-house data initiatives—ranging from complex data analysis and strategic insights to predictive modeling and real-time implementations. You will work closely with cross-functional teams to deliver high-quality, data-driven solutions that drive business impact.
Key Responsibilities
- Develop, implement, and optimize machine learning models for healthcare and internal projects.
- Conduct feature engineering to improve model performance.
- Deliver real-time model predictions and ensure their smooth integration into production systems.
- Collaborate with data scientists, analysts, and product teams to understand requirements and translate them into technical solutions.
- Apply statistical techniques and data analysis to derive insights and recommendations.
- Work with Large Language Models (LLMs) , deep learning architectures, and vector databases where applicable.
- Ensure scalability, efficiency, and reliability of deployed models.
Requirements :
- 1–3 years total professional experience in data or software engineering roles.
- 6–12 months hands-on experience in AI/ML model development and deployment.
- Strong proficiency in Python (mandatory).
- Solid understanding of statistics and its application in data modeling.
- Knowledge of LLMs , deep learning models, and vector databases .
- Experience with feature engineering and implementing real-time predictions.
Machine Learning Engineer
Posted today
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About Hero Vired:
Would you like to be part of an exciting, innovative, and high-growth startup from one of the largest and most well-respected business houses in the country - the Hero Group?
Hero Vired is a premium learning experience offering industry-relevant programs and world-class partnerships, to create the change-makers of tomorrow.
At Hero Vired, we believe everyone is made of big things. With the experience, knowledge, and expertise of the Hero Group, Hero Vired is on a mission to change the way we learn. Hero Vired aims to give learners the knowledge, skills, and expertise through deeply engaged and holistic experiences, closely mapped with industry to empower them to transform their aspirations into reality. The focus will be on disrupting and reimagining university education & skilling for working professionals by offering high-impact online certification and degree programs.
The illustrious and renowned US$5 billion diversified Hero Group is a conglomerate of Indian companies with primary interests and operations in automotive manufacturing, financing, renewable energy, electronics manufacturing, and education. The Hero Group (BML Munjal family) companies include Hero MotoCorp, Hero FinCorp, Hero Future Energies, Rockman Industries, Hero Electronix, Hero Mindmine, and the BML Munjal University.
For detailed information, visit Hero Vired
Role : Machine Learning Engineer(LLM & NLP)
Location: Delhi (Sultanpur)
Job Type: Full Time (Work from Office)
Experience: 3+ years
Function: Technology
About the Role
We are looking for an experienced Machine Learning Engineer with deep expertise in Large Language Models (LLMs) and Natural Language Processing (NLP) to design, build, and deploy cutting-edge AI solutions. The ideal candidate will have hands-on experience in fine-tuning, optimizing, and productionizing LLMs for various education and learning use cases, along with a solid foundation in core NLP concepts and ML engineering practices.
The ideal candidate should be passionate about building and deploying robust ML models, have strong software engineering principles, and work closely with cross-functional teams to integrate AI-powered features into our digital learning products.
Key Responsibilities:
- Build AI-powered agents using LangChain/OpenAI APIs to simulate human-like search, click, scrape, and store behavior
- Use Python scraping frameworks (Scrapy , Playwright , BeautifulSoup ) to extract dynamic web data
- Apply NLP techniques to extract structured fields from unstructured content (e.g., reviews, placement data)
- Design ETL pipelines using Airflow or Prefect to ingest, clean, enrich, and store data
- Store the output in normalized formats in PostgreSQL , Neo4j , or ElasticSearch
- Machine Learning -> Train/update models that improve classification, ranking, or deduplication
- Design a GPT-powered web crawler that uses Google/Bing APIs to simulate top human clicks → summarize pages → extract structured info
- Build a semantic search pipeline using ElasticSearch + OpenAI embeddings
- Architect a Knowledge Graph in Neo4j or TigerGraph for relationship-heavy queries
- Implement LLM feedback loops for content validation, confidence scoring, and hallucination detection
- Build a monitoring dashboard to track data freshness, accuracy, and update intervals
- Familiarity with Reinforcement Learning with Human Feedback (RLHF) or Retrieval-Augmented Generation (RAG)
Machine Learning Engineer
Posted today
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Location: Coimbatore / Remote
Experience: Minimum 3–5 years
Type: Full-Time
About Xlorit
Xlorit, based in Coimbatore, is a premier digital solutions provider specializing in web, app, and UI/UX experiences tailored to meet your needs. Our mission is to simplify success by offering cutting-edge tools, agile expertise, and transparent partnerships. Join us to help businesses thrive by driving efficiency, creating exceptional customer experiences, and staying ahead in the digital era.
Role Overview
We are looking for a skilled and hands-on AI/ML Developer with strong expertise in model fine-tuning, AI system deployment, and hardware optimization. This role focuses on building and implementing AI models. You will work directly on training, optimizing, and deploying large AI models, with an emphasis on performance and scalability.
Key Responsibilities
- Assemble and configure GPU-based hardware environments (e.g., A100, H100, RTX series) for AI workloads.
- Deploy open-source and commercial AI models, including LLMs and SLMs, for high-throughput inference.
- Fine-tune models using techniques such as LoRA, QLoRA, PEFT, and instruction tuning.
- Prepare and preprocess training datasets, including formatting, tokenization, and data cleaning.
- Participate in the complete ML pipeline: training, validation, benchmarking, and evaluation.
- Use tools such as Hugging Face Transformers, vLLM, TGI, DeepSpeed, and Weights & Biases.
Required Qualifications
- 3–5 years of hands-on experience in AI/ML model development and deployment.
- Proficiency in Python and PyTorch.
- Experience with model training, fine-tuning, and hardware optimization.
- Familiarity with LLM architectures and transformer-based models.
- Knowledge of evaluation metrics (e.g., perplexity, BLEU, MMLU, QA-F1).
- Strong understanding of AI system performance tuning and memory-efficient inferencing.
Preferred (Nice to Have)
- Experience with RLHF pipelines, quantization (GGUF, GPTQ), or MLOps practices.
- Exposure to multi-modal models (text, vision, or audio).
- Experience using tools like FastAPI, Docker, or Triton Inference Server.
Ready to join:
If you’re passionate about building innovative solutions and thrive in a collaborative environment, we’d love to hear from you! Please submit your resume detailing your experience and why you would be a great fit for our team.
Machine Learning Engineer
Posted today
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About the Role
MLOps Engineer is responsible to help deploy, scale, and manage machine learning models in production environments. You will work closely with data scientists and engineering teams to automate the machine learning lifecycle, optimize model performance, and ensure smooth integration with data pipelines.
Responsibilities
- Bachelor's degree in computer science, analytics, mathematics, statistics.
- Strong experience in Python, SQL, Pyspark.
- Solid understanding and knowledge of containerization technologies (Docker, Podman, Kubernetes).
- Proficient in CI/CD pipelines, model monitoring, and MLOps platforms (e.g., AWS SageMaker, Azure ML, MLFlow).
- Proficiency in cloud platforms, specifically AWS, Azure and GCP.
- Familiarity with ML frameworks such as TensorFlow, PyTorch, Scikit-learn.
- Familiarity with batch processing integration for large-scale data pipelines.
- Experience with serving models using FastAPI, Flask, or similar frameworks for real-time inference.
- Certifications in AWS, Azure or ML technologies are a plus.
- Experience with Databricks is highly valued.
- Strong problem-solving and analytical skills.
- Ability to work in a team-oriented, collaborative environment.
Qualifications
- Bachelor's degree in computer science, analytics, mathematics, statistics.
Required Skills
- Model Development & Tracking: TensorFlow, PyTorch, scikit-learn, MLflow, Weights & Biases
- Model Packaging & Serving: Docker, Kubernetes, FastAPI, Flask, ONNX, TorchScript
- CI/CD & Pipelines: GitHub Actions, GitLab CI, Jenkins, ZenML, Kubeflow Pipelines, Metaflow
- Infrastructure & Orchestration: Terraform, Ansible, Apache Airflow, Prefect
- Cloud & Deployment: AWS, GCP, Azure, Serverless (Lambda, Cloud Functions)
- Monitoring & Logging: Prometheus, Grafana, ELK Stack, WhyLabs, Evidently AI, Arize
- Testing & Validation: Pytest, unittest, Pydantic, Great Expectations
- Feature Store & Data Handling: Feast, Tecton, Hopsworks, Pandas, Spark, Dask
- Message Brokers & Data Streams: Kafka, Redis Streams
- Vector DB & LLM Integrations (optional): Pinecone, FAISS, Weaviate, LangChain, LlamaIndex, PromptLayer.
Preferred Skills
- Experience with Databricks is highly valued.
- Certifications in AWS, Azure or ML technologies are a plus.
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Machine Learning Engineer
Posted 1 day ago
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Designation: - ML / MLOPs Engineer
Location: - Noida (Sector- 132)
Key Responsibilities:
• Model Development & Algorithm Optimization : Design, implement, and optimize ML
models and algorithms using libraries and frameworks such as TensorFlow , PyTorch , and
scikit-learn to solve complex business problems.
• Training & Evaluation : Train and evaluate models using historical data, ensuring accuracy,
scalability, and efficiency while fine-tuning hyperparameters.
• Data Preprocessing & Cleaning : Clean, preprocess, and transform raw data into a suitable
format for model training and evaluation, applying industry best practices to ensure data
quality.
• Feature Engineering : Conduct feature engineering to extract meaningful features from data
that enhance model performance and improve predictive capabilities.
• Model Deployment & Pipelines : Build end-to-end pipelines and workflows for deploying
machine learning models into production environments, leveraging Azure Machine
Learning and containerization technologies like Docker and Kubernetes .
• Production Deployment : Develop and deploy machine learning models to production
environments, ensuring scalability and reliability using tools such as Azure Kubernetes
Service (AKS) .
• End-to-End ML Lifecycle Automation : Automate the end-to-end machine learning
lifecycle, including data ingestion, model training, deployment, and monitoring, ensuring
seamless operations and faster model iteration.
• Performance Optimization : Monitor and improve inference speed and latency to meet real-
time processing requirements, ensuring efficient and scalable solutions.
• NLP, CV, GenAI Programming : Work on machine learning projects involving Natural
Language Processing (NLP) , Computer Vision (CV) , and Generative AI (GenAI) ,
applying state-of-the-art techniques and frameworks to improve model performance.
• Collaboration & CI/CD Integration : Collaborate with data scientists and engineers to
integrate ML models into production workflows, building and maintaining continuous
integration/continuous deployment (CI/CD) pipelines using tools like Azure DevOps , Git ,
and Jenkins .
• Monitoring & Optimization : Continuously monitor the performance of deployed models,
adjusting parameters and optimizing algorithms to improve accuracy and efficiency.
• Security & Compliance : Ensure all machine learning models and processes adhere to
industry security standards and compliance protocols , such as GDPR and HIPAA .
• Documentation & Reporting : Document machine learning processes, models, and results to
ensure reproducibility and effective communication with stakeholders.Required Qualifications:
• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related
field.
• 3+ years of experience in machine learning operations (MLOps), cloud engineering, or
similar roles.
• Proficiency in Python , with hands-on experience using libraries such as TensorFlow ,
PyTorch , scikit-learn , Pandas , and NumPy .
• Strong experience with Azure Machine Learning services, including Azure ML Studio ,
Azure Databricks , and Azure Kubernetes Service (AKS) .
• Knowledge and experience in building end-to-end ML pipelines, deploying models, and
automating the machine learning lifecycle.
• Expertise in Docker , Kubernetes , and container orchestration for deploying machine
learning models at scale.
• Experience in data engineering practices and familiarity with cloud storage solutions like
Azure Blob Storage and Azure Data Lake .
• Strong understanding of NLP , CV , or GenAI programming, along with the ability to apply
these techniques to real-world business problems.
• Experience with Git , Azure DevOps , or similar tools to manage version control and CI/CD
pipelines.
• Solid experience in machine learning algorithms , model training , evaluation , and
hyperparameter tuning
Machine Learning Engineer
Posted 1 day ago
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Role: ML Engineer (Part time)
Experience- 2- 5 Years
Location: Hyderabad
Job description:
We're seeking a highly skilled Machine Learning Engineer to drive the development and implementation of cutting-edge ML solutions. As a genius with ML, you'll leverage your expertise to design, build, and deploy innovative models and algorithms that solve complex problems and drive business growth.
Key Responsibilities:
1. ML Model Development: Design, train, and deploy machine learning models using various techniques, including deep learning, natural language processing, and computer vision.
2. Innovation Leadership: Lead the development of innovative ML solutions, identifying opportunities for growth and improvement.
3. Collaboration: Work with cross-functional teams to integrate ML solutions into products and services.
4. Research: Stay up-to-date with the latest ML research and trends, applying findings to improve existing solutions and drive innovation.
Requirements:
1. Technical Expertise: Strong background in machine learning, deep learning, and programming languages such as Python, TensorFlow, or PyTorch.
2. Innovation Mindset: Proven ability to think creatively and develop innovative solutions.
3. Collaboration: Excellent communication and collaboration skills.
Nice to Have:
1. Cloud Experience: Experience with cloud platforms such as AWS, Azure, or Google Cloud.
2. Domain Expertise: Knowledge of specific domains, such as healthcare, finance, or computer vision.
What We Offer:
1. Challenging Projects: Opportunities to work on complex, high-impact projects.
2. Collaborative Environment: Dynamic team of experts in ML and related fields.
3. Growth Opportunities: Professional development and growth opportunities.
If you're passionate about machine learning and innovation, we'd love to hear from you!
Machine Learning Specialist
Posted 1 day ago
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Greetings from TCS!
TCS is Hiring for MLOps/LLMOps Consultants
Interview Mode: Virtual
Required Total Experience: 10-18 years
Work location: PAN INDIA
Must have:
Experience in AI/ML deployment
Experience in Generative AI based apps deployment
Excellent knowledge in CI/CD
Good idea about AI/ML based development
Good exposure on cloud infrastructure
Excellent knowledge AI/ML including algorithm development
In-depth knowledge in Data (collection, preparation, analysis, visualization)
Hands-on experience in Python based development
Primary skills required : MLOps & Pipeline Engineering, Model Deployment & Scalability, Model Monitoring & Performance Analysis, AI Infrastructure Management
Secondary skills required: Docker, Kubernetes, Cloud Computing Platforms (AWS, Azure, GCP)
If interested kindly send your updated CV and below mentioned details through DM/E-mail:
Name:
E-mail ID:
Contact Number:
Highest qualification(Fulltime):
Preferred Location:
Highest qualification university:
Current organization:
Total, years of experience:
Relevant years of experience:
Any gap: Mention-No: of months/years (career/ education):
If any then reason for gap:
Is it rebegin:
Previous organization name:
Current CTC:
Expected CTC:
Notice Period:
Have you worked with TCS before (Permanent / Contract):