44 Model Deployment Jobs - Page 2

Description We are seeking an experienced Data Scientist to join our dynamic team in India. The ideal candidate will have 15-22 years of experience in data science and will be responsible for developing predictive models, analyzing complex datasets, and providing insights that drive business decisions. Responsibilities Develop and implement advanced predictive models and algorithms to drive business strategies. Analyze large sets of structured and unstructured data to derive actionable insights. Collaborate with cross-functional teams to understand business requirements and deliver data-driven solutions. Communicate findings to stakeholders through data visualization and presentations. Continuously improve data collection and analysis processes. Skills and Qualifications Proficient in programming languages such as Python, R, or Java. Strong knowledge of statistical analysis and machine learning techniques. Experience with data visualization tools like Tableau or Power BI. Familiarity with big data technologies such as Hadoop or Spark. Solid understanding of SQL and database management systems. Strong analytical and problem-solving skills. Excellent communication and collaboration abilities.

7-10 years of experience in machine learning, deep learning. Experience End-to-end architecture design for machine learning solutions Deployment of AI models into scalable services Staying at the forefront of generative AI advancements Optimizing models for performance and scalability Collaborating with cross-functional teams for successful project delivery Degree in Computer Science, Information Technology, Electrical Engineering, or related field Experience or understanding of machine learning, deep learning, generative AIand MLOps Knowledge of deep learning techniques and frameworks (TensorFlow, PyTorch) Familiarity with cloud platforms, preferably Microsoft Azure A certification in AI or machine learning is advantageous Strong analytical and problem-solving skills Excellent communication and team collaboration abilities

Description We are seeking an experienced AI/ML Engineer to join our dynamic team in India. The ideal candidate will leverage their expertise in machine learning and artificial intelligence to develop innovative solutions that drive business growth. Responsibilities Designing, developing, and deploying machine learning models to solve business problems. Collaborating with cross-functional teams to understand data requirements and deliver actionable insights. Performing data preprocessing, feature engineering, and model validation. Conducting experiments to improve the performance of existing models. Staying up-to-date with the latest research and advancements in AI and ML. Skills and Qualifications Proficiency in programming languages such as Python or R. Strong understanding of machine learning algorithms and frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Experience with data manipulation and analysis using libraries like Pandas and NumPy. Familiarity with cloud platforms (AWS, Azure, GCP) for deploying ML models. Knowledge of statistical analysis and data visualization tools (e.g., Matplotlib, Seaborn). Strong problem-solving skills and ability to work in a team-oriented environment.

Description We are seeking a skilled Deep Learning Engineer to join our team in India. The ideal candidate will have a strong background in machine learning and deep learning techniques, with a passion for developing innovative solutions. You will work on cutting-edge projects and collaborate with a talented team to drive the development of advanced AI applications. Responsibilities Design and implement deep learning models for various applications such as image recognition, natural language processing, and predictive analytics. Collaborate with data scientists and software engineers to integrate deep learning solutions into existing applications. Conduct research to improve existing models and explore new techniques in deep learning and artificial intelligence. Evaluate model performance and optimize algorithms for better accuracy and efficiency. Stay updated with the latest trends and advancements in deep learning and AI technologies. Skills and Qualifications Proficient in programming languages such as Python, R, or Java. Hands-on experience with deep learning frameworks such as TensorFlow, PyTorch, or Keras. Strong understanding of machine learning algorithms and statistical methods. Experience with data preprocessing and data augmentation techniques. Familiarity with cloud platforms like AWS, Azure, or Google Cloud for deploying models. Ability to work with large datasets and knowledge of data manipulation libraries like Pandas and NumPy. Excellent problem-solving skills and the ability to work independently as well as in a team environment.

Role & responsibilities : Leadership & Strategy : Lead and manage a team of 20 Data Scientists (DS), ensuring high performance and continuous growth Define and implement the companys data science vision and strategy Work closely with global business leaders to identify opportunities where data science can drive business value Stay up to date with emerging trends in AI, ML, and advanced data analytics to drive innovation. Ensure all agreed Key Performance Indicators (KPIs) are met in line with performance agreements, maintaining high standards of operational efficiency Data Science : Develop and deploy machine learning models, statistical algorithms and predictive analytics solutions. Ensure the scalability, reliability and efficiency of data science models and pipelines. Collaborate with engineering and data teams to improve data quality, availability and infrastructure Participate in global meets & workshops to review & develop strong process and strategy for DS services in India Utilize advanced analytics to solve complex business problems and improve decision-making Stakeholder Management : Partner with cross-functional teams (engineering, operations) to translate business needs into data-driven solutions Communicate insights and recommendations to both technical and non-technical stakeholders Develop data-driven strategies to optimize customer experience, revenue and operational efficiency Exhibit very strong local and global stakeholders management skill Support in developing proactive proposals and solutions to internal and external stakeholders. Team Development & Mentorship : Recruit, train and mentor Data Scientists, Data Engineers and AI platform engineers, fostering a culture of innovation. Support HR partner with building hiring strategy for the niched skills Conduct performance evaluations, provide feedback and set career development plans for the team members Encourage best practices in coding, model deployment and data governance. Desired candidate profile : Bachelors or Masters or PhD in Data Science, Computer Science, Statistics, Mathematics or a related field. Technical Skills: 10-15 years of total experience with min 5 yrs in data science, analytics, AI/Deep Learning, NLP and Generative AI . Strong proficiency in Python, R, SQL and cloud platforms ( AWS, GCP, or Azure ) Expertise in Machine Learning frameworks ( TensorFlow, PyTorch, Scikit-learn ) Experience with big data technologies (Spark, Hadoop, Databricks) and data engineering concepts. Solid understanding of statistics, probability and optimization techniques. Experience with MLOps, model deployment and productionizing ML models . Industry experience in Aviation, Automotive, Finance, Healthcare, Retail or any IT Technology based domain. Leadership & Business Acumen : • Proven experience in leading and managing data science teams. • Ability to translate business problems into data science solutions. • Strong communication and stakeholder management skills. • Experience in budget planning, resource allocation and project management. • Proficiency in Risk assessment and mitigation planning.

AI Ops Senior Architect 12 -17 Years Work Location - Pune/ Bengaluru/Hyderabad/Chennai/ Gurugram Tredence is Data science, engineering, and analytics consulting company that partners with some of the leading global Retail, CPG, Industrial and Telecom companies. We deliver business impact by enabling last mile adoption of insights by uniting our strengths in business analytics, data science and data engineering. Headquartered in the San Francisco Bay Area, we partner with clients in US, Canada, and Europe. Bangalore is our largest Centre of Excellence with skilled analytics and technology teams serving our growing base of Fortune 500 clients. JOB DESCRIPTION At Tredence, you will lead the evolution of Industrializing AI ” solutions for our clients by implementing ML/LLM/GenAI & Agent Ops best practices. You will lead the Architecture , Design & development of large scale ML/LLMOps platforms for our clients. You’ll build and maintain tools for deployment, monitoring, and operations. You’ll be a trusted advisor to our clients in ML/GenAI/Agent Ops space & coach to the ML engineering practitioners to build effective solutions to Industrialize AI solutions THE IDEAL CANDIDATE WILL BE RESPONSIBLE FOR AI Ops Strategy, Innovation, Research and Technical Standards 1. Conduct research and experiment with emerging AI Ops technologies and trends. Create POV’s, POC’s & present Proof of Technology to use latest tools, Technologies & services from Hyper scalers focussed on ML, GenAI & Agent Ops 2. Define and propose new technical standards and best practices for the organization's AI Ops environment. 3. Lead the evaluation and adoption of innovative MLOps solutions to address critical business challenges. 4. Conduct meet ups, attend & present in Industry events, conferences, etc 5. Ideate & develop accelerators to strengthen service offerings of AI Ops practice Solution Design & Architectural Development 6. Lead Design & architecture of scalable model training & deployment pipelines for large-scale deployments 7. Architect & Design large scale ML & GenAI Ops platforms 8. Collaborate with Data science & GenAI practice to define and implement strategies of AI solutions for model explainability and interpretability 9. Mentor and guide senior architects in crafting cutting-edge AI Ops solutions 10. Lead architecture reviews and identify opportunities for significant optimizations and improvements. Documentation and Best Practices 11. Develop and maintain comprehensive documentation of AIOps architectures designs and best practices. 12. Lead the development and delivery of training materials and workshops on AIOps tools and techniques. 13. Actively participate in sharing knowledge and expertise with the MLOps team through internal presentations and code reviews. Qualifications and Skills: 1. Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field with minimum 12 years of experience 2. Proven experience in architecting & developing AIOps solutions – to streamline Machine Learning & GenAI development lifecycle 3. Proven experience as an AI Ops Architect – ML & GenAI in architecting & design of ML & GenAI platforms 4. Hands on experience in Model deployment strategies, Designing ML & GenAI model pipelines to scale in production, Model Observability techniques used to monitor performance of ML & LLM’s 5. Strong coding skills with experience in implementing best coding practices Technical Skills & Expertise Python, PySpark, PyTorch ,Java, Micro Services, API’s LLMOps – Vector DB, RAG, LLM Orchestration tools, LLM Observability, LLM Guardrails, Responsible AI MLOps - MLFlow, ML/DL libraries, Model & Data Drift Detection libraries & techniques Real Time & Batch Streaming Container Orchestration Platforms Cloud platforms – Azure/ AWS/ GCP, Data Platforms – Databricks/ Snowflake Nice to Have: Understanding of Agent Ops Exposure to Databricks platform You can expect to – Work with world’s biggest Retailers, CPG’s, HealthCare, Banking & Manufacturing customers and help them solve some of their most critical problems Create multi-million Dollar business opportunities by leveraging impact mindset, cutting edge solutions and industry best practices. Work in a diverse environment that keeps evolving Hone your entrepreneurial skills as you contribute to growth of the organization

About Us: At Novus Loyalty, we are committed to building cutting-edge AI-driven solutions that enhance business performance and user experience. We are currently seeking a skilled and passionate AI Engineer to join our team, with a strong emphasis on Azure AI technologies. Key Responsibilities: Design, develop, and deploy AI models using Azure AI services. Work on various AI domains, including Generative AI, Agentic AI, and other advanced ML models. Collaborate with cross-functional teams to integrate AI solutions into production environments. Conduct data analysis and preprocessing to support model development. Monitor and optimize AI model performance and accuracy. Stay up-to-date with emerging AI technologies, tools, and best practices. Required Qualifications: Minimum 3 years of hands-on experience in AI/ML model development. Proven experience with Azure AI services (e.g., Azure Machine Learning, Cognitive Services, Azure OpenAI). Strong programming skills in Python or other relevant languages. Solid understanding of machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Experience with large language models (LLMs), NLP, or generative AI applications is a plus. Familiarity with MLOps practices and cloud-based model deployment. Excellent problem-solving and communication skills.

Develop and deploy ML pipelines using MLOps tools, build FastAPI-based APIs, support LLMOps and real-time inferencing, collaborate with DS/DevOps teams, ensure performance and CI/CD compliance in AI infrastructure projects. Required Candidate profile Experienced Python developer with 4–8 years in MLOps, FastAPI, and AI/ML system deployment. Exposure to LLMOps, GenAI models, containerized environments, and strong collaboration across ML lifecycle

Experience Desired: Front-End Development Skills HTML/CSS/JavaScript Proficiency in the core technologies for building web interfaces. Front-End Frameworks Knowledge of frameworks like React, Angular, or Vue.js for creating interactive and responsive user interfaces. UI/UX Design Basic understanding of user experience and user interface design principles. Back-End Development Skills Server-Side Languages Proficiency in server-side languages such as Python, Node.js,APIs Experience in building and consuming RESTful, Flask / Fast API / GraphQL APIs. Database Management Knowledge of SQL and NoSQL databases, including MySQL, PostgreSQL, MongoDB, etc. DevOps and Cloud Skills Containerization and Orchestration Experience with Docker and Kubernetes / OpenShift for containerization and orchestration of applications. CI/CD Pipelines Knowledge of continuous integration and continuous deployment tools and practices. Security Best Practices understanding of security principles and best practices for protecting data and systems, including IAM, encryption and network Security. Cloud Services Familiarity with cloud platforms like AWS, Google Cloud, or Azure for deploying and managing applications and AI models. AI and Machine Learning Skills (Good to have) Foundations in Machine Learning and Deep Learning Understanding algorithms, neural networks, supervised and unsupervised learning, and deep learning frameworks like TensorFlow, PyTorch, and Keras. Generative Models Knowledge of generative models such as GANs (Generative Adversarial Networks), VAEs (Variational Autoencoders), and Transformers. Natural Language Processing (NLP)Knowledge in NLP techniques and libraries (e.g., spaCy, NLTK, Hugging Face Transformers) for text generation tasks. Model Deployment Experience with deploying models using services like TensorFlow Serving, TorchServe, or cloud-based solutions (e.g., AWS SageMaker, Google AI Platform). Basic understanding of implementing Prompt Engineering, Finetuning and RAG. Additional Skills Version Control Proficiency with Git and version control workflows. Software Development Practices APIUnderstanding of agile methodologies, testing, and code review practices.

Experience Desired: Front-End Development Skills HTML/CSS/JavaScript Proficiency in the core technologies for building web interfaces. Front-End Frameworks Knowledge of frameworks like React, Angular, or Vue.js for creating interactive and responsive user interfaces. UI/UX Design Basic understanding of user experience and user interface design principles. Back-End Development Skills Server-Side Languages Proficiency in server-side languages such as Python, Node.js,APIs Experience in building and consuming RESTful, Flask / Fast API / GraphQL APIs. Database Management Knowledge of SQL and NoSQL databases, including MySQL, PostgreSQL, MongoDB, etc. DevOps and Cloud Skills Containerization and Orchestration Experience with Docker and Kubernetes / OpenShift for containerization and orchestration of applications. CI/CD Pipelines Knowledge of continuous integration and continuous deployment tools and practices. Security Best Practices understanding of security principles and best practices for protecting data and systems, including IAM, encryption and network Security. Cloud Services Familiarity with cloud platforms like AWS, Google Cloud, or Azure for deploying and managing applications and AI models. AI and Machine Learning Skills (Good to have) Foundations in Machine Learning and Deep Learning Understanding algorithms, neural networks, supervised and unsupervised learning, and deep learning frameworks like TensorFlow, PyTorch, and Keras. Generative Models Knowledge of generative models such as GANs (Generative Adversarial Networks), VAEs (Variational Autoencoders), and Transformers. Natural Language Processing (NLP)Knowledge in NLP techniques and libraries (e.g., spaCy, NLTK, Hugging Face Transformers) for text generation tasks. Model Deployment Experience with deploying models using services like TensorFlow Serving, TorchServe, or cloud-based solutions (e.g., AWS SageMaker, Google AI Platform). Basic understanding of implementing Prompt Engineering, Finetuning and RAG. Additional Skills Version Control Proficiency with Git and version control workflows. Software Development Practices APIUnderstanding of agile methodologies, testing, and code review practices.

AI engineer Proficiency in programming languages such as Python, Java, or R with at least 3 yrs exp. Experience with machine learning frameworks like TensorFlow, PyTorch, or Scikit-learn. Familiarity with cloud platforms (e.g., AWS, GCP, Azure) for model deployment and scaling. Understanding of financial data structures and databases.

Curious about the role? What your typical day would look like? 6+ years of relevant DS experience Proficient in a structured Python Proficient in any one of cloud technologies is mandatory (AWS/ Azure/GCP) Follows good software engineering practices and has an interest in building reliable and robust software Good understanding of DS concepts and DS model lifecycle Working knowledge of Linux or Unix environments ideally in a cloud environment Working knowledge of Spark/ PySpark is desirable Model deployment / model monitoring experience is mandatory CI/CD pipeline creation is good to have Excellent written and verbal communication skills

We are looking for a skilled AI/ML Engineer with expertise in Python, PyTorch, TensorFlow, and YOLO to join our team at Evnek Technologies Pvt Ltd. The candidate should have a solid understanding of deep learning and computer vision, and should be capable of developing and deploying models for real-world applications. Responsibilities include working on object detection, training and optimizing models, handling large datasets, and integrating AI into web solutions. Experience with Docker, FastAPI, React.js, and Node.js is a plus. Familiarity with cloud platforms like AWS/GCP/Azure is preferred. This is a remote position. Location- Remote,Delhi NCR,Bengaluru,Chennai,Pune,Kolkata,Ahmedabad, Mumbai,Hyderabad Education- Bachelors Degree in Computer Science, Information Systems, or a related field

Work mode – Currently this is remote (WFH) but it’s not permanent WFH , once business ask the candidate to come to office, they must relocate. Mandatory:- ML Engineer, MLOPS , end to end deployment, CI/CD, Docker and Kubernetes, model deployment Required Candidate profile Lead end-to-end development & delivery of Machine-Learning applications, emphasizing operations and monitoring. Deployment and operation of ML applications, following CI/CD best practices.

We are seeking a highly experienced and strategic Senior Manager Applied Science to lead and scale our applied research and machine learning initiatives. This role involves working at the intersection of cutting-edge AI/ML technologies and real-world business challenges to drive measurable impact. Key Responsibilities: Lead a team of applied scientists and machine learning engineers to develop scalable AI/ML models. Define and drive the scientific vision, strategy, and roadmap aligned with business goals. Collaborate cross-functionally with product, engineering, and analytics teams. Stay ahead of emerging technologies and apply them to solve complex business problems. Publish research, file patents, or present findings in internal/external forums as needed. Requirements: 10+ years of experience in applied science, machine learning, or data science roles. Strong background in statistics, optimization, deep learning, NLP, or related fields. Hands-on experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn. Proven experience in leading high-performance technical teams. Advanced degree (Ph.D. or Master’s) in Computer Science, Mathematics, Statistics, or a related field. Excellent communication and leadership skills. Preferred Qualifications: Experience in a product-led tech company or research lab environment. Track record of deploying ML models in production. Publications or patents in relevant areas.

Notice Period: Candidates with up to 1-month notice preferred Findability Sciences is looking for a hands-on AI expert with experience in developing and implementing comprehensive predictive and generative AI solutions. This is a core technical role rather than a support-based one. What we are looking for: 3+ years of experience in AI/ML with a Masters or Ph.D. in a relevant field Strong knowledge of Python, SQL, Machine Learning, LLMs, RAG, and Prompt Engineering Experience in predictive modeling, time series forecasting, and generative AI use cases Experience with ML Ops workflows model deployment, monitoring, versioning, and pipeline automation Key Responsibilities: Design and deploy predictive & GenAI solutions for real-world business use cases Build and optimize LLM-based workflows for summarization, retrieval, and Q&A Collaborate with cross-functional teams to define use cases and develop proof-of-concepts Translate business problems into ML/GenAI solutions and deliver outcomes Validate, compare, and optimize models for performance and scalability Apply basic ML Ops practices to ensure smooth deployment and monitoring of models Contribute to reusable pipelines, prompt tuning strategies, and production integration Present actionable insights and models to stakeholders clearly and effectively

What would you do? System Design: Architect and design end-to-end speech processing pipelines, from data acquisition to model deployment. Ensure systems are scalable, efficient, and maintainable. Advanced Modeling: Develop and implement advanced machine learning models for speech recognition, speaker diarization, and related tasks. Utilize state-of-the-art techniques such as deep learning, transfer learning, and ensemble methods. Research and Development: Conduct research to explore new methodologies and tools in the field of speech processing. Publish findings and present at industry conferences. Performance Optimization: Continuously monitor and optimize system performance, focusing on accuracy, latency, and resource utilization. Collaboration: Work closely with product management, data science, and software engineering teams to define project requirements and deliver innovative solutions. Customer Interaction: Engage with customers to understand their needs and provide tailored speech solutions. Assist in troubleshooting and optimizing deployed systems. Documentation and Standards: Establish and enforce best practices for code quality, documentation, and model management within the team. Required Skills 2+ years of experience in speech processing, machine learning, and model deployment. Demonstrated expertise in leading projects and teams. Technical skills: • Excellent knowledge in Python / Java programming. • In-depth knowledge of speech processing frameworks like, Wave2vec, Kaldi, HTK, DeepSpeech and Whisper. • Experience with NLP, STT, Speech to Speech LLMs and frameworks like Nvidia NEMO, PyAnnote. • Proficiency in Python and machine learning libraries such as TensorFlow, PyTorch, or Keras. • Experience with large-scale ASR systems, speaker recognition, and diarization algorithms. • Strong understanding of neural networks, sequence-to-sequence models, transformers and attention mechanisms. • Familiarity with NLP techniques and their integration with speech systems. • Expertise in deploying models on cloud platforms and optimizing for real-time applications. Good to have: • Experience with low-latency streaming ASR systems. • Knowledge of speech synthesis, STT (Speech-to-Text) and TTS (Text-to-Speech) systems. • Experience in multilingual and low-resource speech processing.

We are looking for an AI & Machine Learning Lead Engineer to lead the development and deployment of advanced AI and machine learning models. The ideal candidate will have a strong background in precision learning, large language models (LLMs), retrieval-augmented generation (RAG), natural language processing (NLP), and statistical methods for output analysis. This role involves leading a team of engineers and data scientists, setting strategic directions for AI/ML initiatives, and ensuring the delivery of impactful solutions that align with our business objectives. Key Responsibilities: Leadership and Strategy: Lead and manage a team of AI and machine learning engineers, providing technical guidance and mentorship. Oversee the entire machine learning lifecycle, from data collection and preprocessing to model training, evaluation, and deployment. Develop and drive the AI/ML strategy, aligning it with overall business goals. Collaborate with cross-functional teams, including data engineering, product management, and software development, to integrate ML models into production environments. Precision Learning and Large Language Models (LLMs): Design, develop, and optimize precision learning algorithms for specific business applications. Lead efforts in developing, fine-tuning, and deploying large language models (LLMs) to address various use cases such as text generation, summarization, translation, and conversational AI. Retrieval-Augmented Generation (RAG): Implement and optimize RAG systems to improve the performance and accuracy of AI solutions. Develop retrieval strategies that effectively integrate large-scale knowledge bases with LLMs to generate more accurate and contextually relevant outputs. Natural Language Processing (NLP): Develop and implement NLP models for tasks such as text classification, sentiment analysis, named entity recognition, summarization, and question-answering. Stay current with NLP research trends and advancements, implementing best practices to enhance model efficiency and performance. Output Analysis through Statistical Methods: Analyse model outputs using advanced statistical methods to ensure reliability, accuracy, and explainability. Implement A/B testing, hypothesis testing, and other statistical techniques to validate model performance and derive actionable insights. Research and Development: Stay abreast of the latest research in machine learning, deep learning, and AI. Propose and implement novel approaches to solve challenging problems. Collaborate with academic and research institutions to contribute to the machine learning community through publications, open-source projects, and conferences MLOps and Model Deployment: Collaborate with DevOps and data engineering teams to implement MLOps practices for CI/CD pipelines, model monitoring, and governance. Ensure scalable deployment of AI/ML models on cloud platforms (AWS, GCP, Azure) or on-premises environments. Mentorship and Team Leadership: Mentor and guide a team of machine learning engineers and data scientists, fostering a culture of continuous learning and innovation. Conduct regular code reviews, provide constructive feedback, and ensure adherence to best practices in machine learning. Required Qualifications: 8-10 years Experience with Bachelors or Masters degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field; PhD is a plus. 5+ years of experience in machine learning and AI, with a strong focus on NLP, LLMs, RAG, and precision learning. Proven track record of leading AI/ML teams and projects from conception to deployment. Expertise in Python and relevant ML libraries/frameworks such as TensorFlow, PyTorch, scikit-learn, and Hugging Face Transformers. Strong understanding of NLP techniques, including transformer architectures (e.g., BERT, GPT). Experience in RAG techniques, knowledge retrieval systems, and integrating LLMs with external data sources. Proficiency in statistical analysis and hypothesis testing, with a strong foundation in experimental design. Excellent problem-solving skills, with the ability to articulate complex technical concepts to non-technical stakeholders. Preferred Qualifications: Experience with cloud services (AWS, GCP, Azure) for model deployment and scaling. Familiarity with MLOps practices, including model versioning, monitoring, and CI/CD pipelines for ML. Knowledge of advanced AI techniques such as reinforcement learning, meta-learning, and unsupervised learning. Strong publication record or contributions to the AI/ML community.

MLE/Sr. MLE Chennai, Bangalore, Hyderabad Who we are Tiger Analytics is a global leader in AI and analytics, helping Fortune 1000 companies solve their toughest challenges. We offer full-stack AI and analytics services & solutions to empower businesses to achieve real outcomes and value at scale. We are on a mission to push the boundaries of what AI and analytics can do to help enterprises navigate uncertainty and move forward decisively. Our purpose is to provide certainty to shape a better tomorrow. Our team of 4000+ technologists and consultants are based in the US, Canada, the UK, India, Singapore and Australia, working closely with clients across CPG, Retail, Insurance, BFS, Manufacturing, Life Sciences, and Healthcare. Many of our team leaders rank in Top 10 and 40 Under 40 lists, exemplifying our dedication to innovation and excellence. We are a Great Place to Work-Certified (2022-25), recognized by analyst firms such as Forrester, Gartner, HFS, Everest, ISG and others. We have been ranked among the Best and Fastest Growing analytics firms lists by Inc., Financial Times, Economic Times and Analytics India Magazine. Curious about the role? What your typical day would look like? We are looking for a Machine Learning Engineer/Sr MLE who will work on a broad range of cutting-edge data analytics and machine learning problems across a variety of industries. More specifically, you will Engage with clients to understand their business context. Translate business problems and technical constraints into technical requirements for the desired analytics solution. Collaborate with a team of data scientists and engineers to embed AI and analytics into the business decision processes. What do we expect? 6+ years of experience with at least 4+ years of relevant MLOps experience. Proficient in a structured Python (Mandate) Proficient in Azure Databricks Follows good software engineering practices and has an interest in building reliable and robust software. Good understanding of DS concepts and DS model lifecycle. Working knowledge of Linux or Unix environments ideally in a cloud environment. Working knowledge of Spark/ PySpark is desirable. Model deployment / model monitoring experience is desirable. CI/CD pipeline creation is good to have. Excellent written and verbal communication skills. B.Tech from Tier-1 college / M.S or M. Tech is preferred. You are important to us, lets stay connected! Every individual comes with a different set of skills and qualities so even if you dont tick all the boxes for the role today, we urge you to apply as there might be a suitable/unique role for you tomorrow. We are an equal-opportunity employer. Our diverse and inclusive culture and values guide us to listen, trust, respect, and encourage people to grow the way they desire. Note: The designation will be commensurate with expertise and experience. Compensation packages are among the best in the industry. Additional Benefits: Health insurance (self & family), virtual wellness platform, and knowledge communities.