As a global leader in cybersecurity, CrowdStrike protects the people, processes and technologies that drive modern organizations. Since 2011, our mission hasn’t changed — we’re here to stop breaches, and we’ve redefined modern security with the world’s most advanced AI-native platform. We work on large scale distributed systems, processing almost 3 trillion events per day. We have 3.44 PB of RAM deployed across our fleet of C* servers - and this traffic is growing daily. Our customers span all industries, and they count on CrowdStrike to keep their businesses running, their communities safe and their lives moving forward. We’re also a mission-driven company. We cultivate a culture that gives every CrowdStriker both the flexibility and autonomy to own their careers. We’re always looking to add talented CrowdStrikers to the team who have limitless passion, a relentless focus on innovation and a fanatical commitment to our customers, our community and each other. Ready to join a mission that matters? The future of cybersecurity starts with you. About The Role The charter of the Data + ML Platform team is to harness all the data that is ingested and cataloged within the Data LakeHouse for exploration, insights, model development, ML Engineering and Insights Activation. This team is situated within the larger Data Platform group, which serves as one of the core pillars of our company. We process data at a truly immense scale. Our processing is composed of various facets including threat events collected via telemetry data, associated metadata, along with IT asset information, contextual information about threat exposure based on additional processing, etc. These facets comprise the overall data platform, which is currently over 200 PB and maintained in a hyper scale Data Lakehouse, built and owned by the Data Platform team. The ingestion mechanisms include both batch and near real-time streams that form the core Threat Analytics Platform used for insights, threat hunting, incident investigations and more. As an engineer in this team, you will play an integral role as we build out our ML Experimentation Platform from the ground up. You will collaborate closely with Data Platform Software Engineers, Data Scientists & Threat Analysts to design, implement, and maintain scalable ML pipelines that will be used for Data Preparation, Cataloging, Feature Engineering, Model Training, and Model Serving that influence critical business decisions. You’ll be a key contributor in a production-focused culture that bridges the gap between model development and operational success. Future plans include generative AI investments for use cases such as modeling attack paths for IT assets. What You’ll Do Help design, build, and facilitate adoption of a modern Data+ML platform Modularize complex ML code into standardized and repeatable components Establish and facilitate adoption of repeatable patterns for model development, deployment, and monitoring Build a platform that scales to thousands of users and offers self-service capability to build ML experimentation pipelines Leverage workflow orchestration tools to deploy efficient and scalable execution of complex data and ML pipelines Review code changes from data scientists and champion software development best practices Leverage cloud services like Kubernetes, blob storage, and queues in our cloud first environment What You’ll Need B.S. in Computer Science, Data Science, Statistics, Applied Mathematics, or a related field and 7 + years related experience; or M.S. with 5+ years of experience; or Ph.D with 6+ years of experience. 3+ years experience developing and deploying machine learning solutions to production. Familiarity with typical machine learning algorithms from an engineering perspective (how they are built and used, not necessarily the theory); familiarity with supervised / unsupervised approaches: how, why, and when and labeled data is created and used 3+ years experience with ML Platform tools like Jupyter Notebooks, NVidia Workbench, MLFlow, Ray, Vertex AI etc. Experience building data platform product(s) or features with (one of) Apache Spark, Flink or comparable tools in GCP. Experience with Iceberg is highly desirable. Proficiency in distributed computing and orchestration technologies (Kubernetes, Airflow, etc.) Production experience with infrastructure-as-code tools such as Terraform, FluxCD Expert level experience with Python; Java/Scala exposure is recommended. Ability to write Python interfaces to provide standardized and simplified interfaces for data scientists to utilize internal Crowdstrike tools Expert level experience with CI/CD frameworks such as GitHub Actions Expert level experience with containerization frameworks Strong analytical and problem solving skills, capable of working in a dynamic environment Exceptional interpersonal and communication skills. Work with stakeholders across multiple teams and synthesize their needs into software interfaces and processes. Experience With The Following Is Desirable Go Iceberg Pinot or other time-series/OLAP-style database Jenkins Parquet Protocol Buffers/GRPC VJ1 Benefits Of Working At CrowdStrike Remote-friendly and flexible work culture Market leader in compensation and equity awards Comprehensive physical and mental wellness programs Competitive vacation and holidays for recharge Paid parental and adoption leaves Professional development opportunities for all employees regardless of level or role Employee Resource Groups, geographic neighbourhood groups and volunteer opportunities to build connections Vibrant office culture with world class amenities Great Place to Work Certified™ across the globe CrowdStrike is proud to be an equal opportunity employer. We are committed to fostering a culture of belonging where everyone is valued for who they are and empowered to succeed. We support veterans and individuals with disabilities through our affirmative action program. CrowdStrike is committed to providing equal employment opportunity for all employees and applicants for employment. The Company does not discriminate in employment opportunities or practices on the basis of race, color, creed, ethnicity, religion, sex (including pregnancy or pregnancy-related medical conditions), sexual orientation, gender identity, marital or family status, veteran status, age, national origin, ancestry, physical disability (including HIV and AIDS), mental disability, medical condition, genetic information, membership or activity in a local human rights commission, status with regard to public assistance, or any other characteristic protected by law. We base all employment decisions--including recruitment, selection, training, compensation, benefits, discipline, promotions, transfers, lay-offs, return from lay-off, terminations and social/recreational programs--on valid job requirements. If you need assistance accessing or reviewing the information on this website or need help submitting an application for employment or requesting an accommodation, please contact us at recruiting@crowdstrike.com for further assistance. Show more Show less

Job Summary: We are looking for highly motivated and analytical Machine Learning Engineers with 1–3 years of experience in building scalable, production-ready AI/ML models. This role involves working on complex business problems using advanced ML/DL techniques across domains such as Natural Language Processing (NLP), Computer Vision, Time Series Forecasting, and Generative AI. You will be responsible for end-to-end model development, deployment, and performance tracking while collaborating with cross-functional teams including data engineering, DevOps, and product. Location: Noida / Gurugram / Indore / Bengaluru / Pune / Hyderabad Experience: 1–3 Years Education: BE / B.Tech / M.Tech / MCA / M.Com Key Responsibilities: Model Development & Experimentation Design and build machine learning models for NLP, computer vision, and time series prediction using supervised, unsupervised, and deep learning techniques. Conduct experiments to improve model performance via architectural modifications, hyperparameter tuning, and feature selection. Apply statistical analysis to validate and interpret model results. Evaluate models using appropriate metrics (e.g., accuracy, precision, recall, F1-score, AUC-ROC). Data Handling & Feature Engineering Process large structured and unstructured datasets using Python, Pandas, and DataFrame APIs. Perform feature extraction, transformation, and selection tailored to specific ML problems. Implement data augmentation and enrichment techniques to enhance training quality. Model Deployment & Productionization Deploy trained models to production environments using cloud platforms such as AWS (especially SageMaker). Containerize models using Docker and orchestrate deployments with Kubernetes. Implement monitoring, logging, and automated retraining pipelines for model health tracking. Collaboration & Innovation Collaborate with data engineers and architects to ensure smooth data flow and infrastructure alignment. Explore and adopt cutting-edge AI/ML methodologies and GenAI frameworks (e.g., LangChain, GPT-3). Contribute to documentation, versioning, and knowledge-sharing across teams. Drive innovation and continuous improvement in AI/ML delivery and engineering practices. Mandatory Technical Skills: Languages & Tools: Python (Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch) Model Development: Deep Learning, NLP, Time Series, Computer Vision Cloud Platforms: AWS (especially SageMaker) Model Deployment: Docker, Kubernetes, REST APIs ML Ops: Model monitoring, performance logging, CI/CD Frameworks: LangChain (for GenAI), Transformers, Hugging Face Preferred / Good to Have: Experience with Foundation Model tuning and prompt engineering Hands-on with Generative AI (GPT-3/4, OpenAI APIs, LangChain integrations) Certifications: AWS Certified Machine Learning – Specialty Experience with version control (Git), and experiment tracking tools (MLflow, Weights & Biases) Soft Skills: Excellent communication and presentation abilities Strong analytical and problem-solving mindset Ability to work in collaborative, fast-paced environments Curiosity to learn emerging technologies and apply them to real-world problems Show more Show less

Job Title: AI/ML Developer (5 Years Experience) Location : Remote Job Type : Full-time Experience:5 Year Job Summary: We are looking for an experienced AI/ML Developer with at least 5 years of hands-on experience in designing, developing, and deploying machine learning models and AI-driven solutions. The ideal candidate should have strong knowledge of machine learning algorithms, data preprocessing, model evaluation, and experience with production-level ML pipelines. Key Responsibilities Model Development : Design, develop, train, and optimize machine learning and deep learning models for classification, regression, clustering, recommendation, NLP, or computer vision tasks. Data Engineering : Work with data scientists and engineers to preprocess, clean, and transform structured and unstructured datasets. ML Pipelines : Build and maintain scalable ML pipelines using tools such as MLflow, Kubeflow, Airflow, or SageMaker. Deployment : Deploy ML models into production using REST APIs, containers (Docker), or cloud services (AWS/GCP/Azure). Monitoring and Maintenance : Monitor model performance and implement retraining pipelines or drift detection techniques. Collaboration : Work cross-functionally with data scientists, software engineers, and product managers to integrate AI capabilities into applications. Research and Innovation : Stay current with the latest advancements in AI/ML and recommend new techniques or tools where applicable. Required Skills & Qualifications Bachelor's or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field. Minimum 5 years of experience in AI/ML development. Proficiency in Python and ML libraries such as Scikit-learn, TensorFlow, PyTorch, XGBoost, or LightGBM. Strong understanding of statistics, data structures, and ML/DL algorithms. Experience with cloud platforms (AWS/GCP/Azure) and deploying ML models in production. Experience with CI/CD tools and containerization (Docker, Kubernetes). Familiarity with SQL and NoSQL databases. Excellent problem-solving and communication skills. Preferred Qualifications Experience with NLP frameworks (e.g., Hugging Face Transformers, spaCy, NLTK). Knowledge of MLOps best practices and tools. Experience with version control systems like Git. Familiarity with big data technologies (Spark, Hadoop). Contributions to open-source AI/ML projects or publications in relevant fields. Show more Show less

osition: Data Scientist Location: Chennai, India (Work from Office) Experience: 2–5 years About the Opportunity: Omnihire is seeking a Data Scientist to join a leading AI-driven data‐solutions company. As part of the Data Consulting team, you’ll collaborate with scientists, IT, and engineering to solve high-impact problems and deliver actionable insights. Key Responsibilities: Analyze large, structured and unstructured datasets (SQL, Hadoop/Spark) to extract business-critical insights Build and validate statistical models (regression, classification, time-series, segmentation) and machine-learning algorithms (Random Forest, Boosting, SVM, KNN) Develop deep-learning solutions (CNN, RNN, LSTM, transfer learning) and apply NLP techniques (tokenization, stemming/lemmatization, NER, LSA) Write production-quality code in Python and/or R using libraries (scikit-learn, TensorFlow/PyTorch, pandas, NumPy, NLTK/spaCy) Collaborate with cross-functional teams to scope requirements, propose analytics solutions, and present findings via clear visualizations (Power BI, Matplotlib) Own end-to-end ML pipelines: data ingestion → preprocessing → feature engineering → model training → evaluation → deployment Contribute to solution proposals and maintain documentation for data schemas, model architectures, and experiment tracking (Git, MLflow) Required Qualifications: Bachelor’s or Master’s in Computer Science, Statistics, Mathematics, Data Science, or a related field 2–5 years of hands-on experience as a Data Scientist (or similar) in a data-driven environment Proficiency in Python and/or R for statistical modeling and ML Strong SQL skills and familiarity with Big Data platforms (e.g., Hadoop, Apache Spark) Demonstrated experience building, validating, and deploying ML/DL models in production or staging Excellent problem-solving skills, attention to detail, and ability to communicate technical concepts clearly Self-starter who thrives in a collaborative, Agile environment Nice-to-Have: Active GitHub/Kaggle portfolio showcasing personal projects or contributions Exposure to cloud-based ML services (Azure ML Studio, AWS SageMaker) and containerization (Docker) Familiarity with advanced NLP frameworks (e.g., Hugging Face Transformers) or production monitoring tools (Azure Monitor, Prometheus) Why Join? Work on high-impact AI/ML projects that drive real business value Rapid skill development with exposure to cutting-edge technologies Collaborative, Agile culture with mentorship from senior data scientists Competitive compensation package and comprehensive benefits Show more Show less

About Amgen Join Amgen’s Mission of Serving Patients At Amgen, if you feel like you’re part of something bigger, it’s because you are. Our shared mission—to serve patients living with serious illnesses—drives all that we do. Since 1980, we’ve helped pioneer the world of biotech in our fight against the world’s toughest diseases. With our focus on four therapeutic areas –Oncology, Inflammation, General Medicine, and Rare Disease– we reach millions of patients each year. As a member of the Amgen team, you’ll help make a lasting impact on the lives of patients as we research, manufacture, and deliver innovative medicines to help people live longer, fuller happier lives. Our award-winning culture is collaborative, innovative, and science based. If you have a passion for challenges and the opportunities that lay within them, you’ll thrive as part of the Amgen team. Join us and transform the lives of patients while transforming your career. Data Scientist What You Will Do The Global Quality Analytics and Innovation team leads the digital transformation and innovation effort throughout Amgen’s Quality organization. We are at the forefront of developing and rolling out data-centric digital tools, employing automation, artificial intelligence (AI), and generative AI to drive end-to-end quality transformation. We are seeking a highly motivated and experienced Data Scientist with a strong background in Generative AI, Large Language Models (LLMs), and MLOps, along with an understanding for Quality in regulated environments (e.g., GxP). This role will play a key part in designing, developing, and deploying scalable AI/ML solutions to drive innovation, efficiency, and regulatory compliance across the organization. You will collaborate with cross-functional teams, including software engineers, data engineers, business stakeholders, and quality professionals to deliver AI-driven capabilities that support strategic business objectives. The ideal candidate is an analytical thinker with excellent technical depth, communication skills, and the ability to thrive in a fast-paced, agile environment. Key Responsibilities Design, build, and deploy generative AI and LLM-based applications using frameworks such as LangChain, LlamaIndex, and others. Engineer reusable and effective prompts for LLMs like OpenAI GPT-4, Anthropic Claude, etc. Develop and maintain evaluation metrics and frameworks for prompt engineering. Conduct data quality assessments, data cleansing, and ingestion of unstructured documents into vector databases. Build retrieval algorithms for relevant data identification to support LLMs and AI applications. Ensure AI/ML development complies with GxP and other regulatory standards, fostering a strong Quality culture. Partner with global and local teams to support regulatory inspection readiness and future technological capabilities in AI. Share insights and findings with team members in an Agile (SAFe) environment. What We Expect Of You Basic Qualifications: Master’s degree and 2 – 4 years of experience in Software Engineering, Data Science, or ML Engineering or Bachelor’s degree and 3 to 5 years of experience in Software Engineering, Data Science, or ML Engineering or Diploma and 7 to 9 years of experience in Software Engineering, Data Science, or ML Engineering Preferred Qualifications: Experience in developing and deploying LLM applications. Strong foundation in ML algorithms, data science workflows, and NLP. Expertise in Python and ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn). Familiarity with MLOps tools (e.g., MLflow, CI/CD, version control). Experience with cloud platforms (AWS, Azure, GCP) and tools like Spark, Databricks. Understanding of RESTful APIs and frameworks like FastAPI. Experience with BI and visualization tools (e.g., Tableau, Streamlit, Dash). Knowledge of GxP compliance and experience working in regulated environments. Strong communication skills with the ability to explain complex topics to diverse audiences. High degree of initiative, self-motivation, and ability to work in global teams. What You Can Expect Of Us As we work to develop treatments that take care of others, we also work to care for your professional and personal growth and well-being. From our competitive benefits to our collaborative culture, we’ll support your journey every step of the way. Apply now and make a lasting impact with the Amgen team. careers.amgen.com As an organization dedicated to improving the quality of life for people around the world, Amgen fosters an inclusive environment of diverse, ethical, committed and highly accomplished people who respect each other and live the Amgen values to continue advancing science to serve patients. Together, we compete in the fight against serious disease. Amgen is an Equal Opportunity employer and will consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status, or any other basis protected by applicable law. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation. Show more Show less

Techvantage.ai is a next-generation technology and product engineering company at the forefront of innovation in Generative AI, Agentic AI , and autonomous intelligent systems . We build intelligent, cutting-edge solutions designed to scale and evolve with the future of artificial intelligence. Role Overview: We are looking for a skilled and versatile AI Infrastructure Engineer (DevOps/MLOps) to build and manage the cloud infrastructure, deployment pipelines, and machine learning operations behind our AI-powered products. You will work at the intersection of software engineering, ML, and cloud architecture to ensure that our models and systems are scalable, reliable, and production-ready. Key Responsibilities: Design and manage CI/CD pipelines for both software applications and machine learning workflows. Deploy and monitor ML models in production using tools like MLflow, SageMaker, Vertex AI, or similar. Automate the provisioning and configuration of infrastructure using IaC tools (Terraform, Pulumi, etc.). Build robust monitoring, logging, and alerting systems for AI applications. Manage containerized services with Docker and orchestration platforms like Kubernetes . Collaborate with data scientists and ML engineers to streamline model experimentation, versioning, and deployment. Optimize compute resources and storage costs across cloud environments (AWS, GCP, or Azure). Ensure system reliability, scalability, and security across all environments. Requirements: 5+ years of experience in DevOps, MLOps , or infrastructure engineering roles. Hands-on experience with cloud platforms ( AWS, GCP, or Azure ) and services related to ML workloads. Strong knowledge of CI/CD tools (e.g., GitHub Actions, Jenkins, GitLab CI). Proficiency in Docker , Kubernetes , and infrastructure-as-code frameworks. Experience with ML pipelines , model versioning, and ML monitoring tools. Scripting skills in Python , Bash , or similar for automation tasks. Familiarity with monitoring/logging tools (Prometheus, Grafana, ELK, CloudWatch, etc.). Understanding of ML lifecycle management and reproducibility. Preferred Qualifications: Experience with Kubeflow , MLflow , DVC , or Triton Inference Server . Exposure to data versioning , feature stores , and model registries . Certification in AWS/GCP DevOps or Machine Learning Engineering is a plus. Background in software engineering, data engineering, or ML research is a bonus. What We Offer: Work on cutting-edge AI platforms and infrastructure Cross-functional collaboration with top ML, research, and product teams Competitive compensation package – no constraints for the right candidate Show more Show less

Company Description Winbold is a startup working on a AI driven investment platform. Job Description This requires immediate joining. Do not apply if you have notice period. We are looking for a very motivated Data Science and Machine Learning Engineer with hands-on experience in feature engineering, model training and building models that run and provide real-time predictions and forecasts. The candidate must be well versed with the following: ML Packages - sklean, xgboost, timeseries models Feature engineering and feature stores MLFlow for Model experimentation Model visualization Model deployment in Cloud and in hosted environments at scale For immediate consideration you can send email to me directly with a note on why you think you are the better suited for this role at madhu at winbolddatasystems.com Qualifications We dont care what degree you have or if you have one. We want a hands-on developer who can get shit done. Additional Information All your information will be kept confidential according to EEO guidelines. Show more Show less

droppGroup is hiring an exceptionally capable AI Engineer with deep, practical expertise in generative AI and natural language processing (NLP). This role is not for generalists, we are looking for specialists who can operate across the full AI lifecycle: from research implementation to real-time production deployment. You must bring a disciplined engineering mindset, state-of-the-art awareness, and hands-on experience with training, fine-tuning, and deploying large language models at scale. Responsibilities Design and fine-tune large transformer models for complex generative tasks including chat, summarization, and semantic understanding. Build LLM-based systems using advanced prompt engineering, retrieval-augmented generation (RAG), and optimized inference. Own the development and optimization of model training pipelines using PyTorch, Hugging Face, DeepSpeed, and related frameworks. Deploy and maintain LLMs in high-performance production environments, optimizing for latency, cost, and stability. Conduct rigorous evaluation of models using benchmarks, human feedback, and automated testing. Manage end-to-end AI workflows with robust versioning, reproducibility, and observability using MLOps tooling. Implement scalable vector databases and semantic search infrastructure for embedding-based retrieval systems. Translate latest AI research into efficient, production-grade code—no research-only profiles. Size, allocate, and optimize compute resources (CPU/GPU/TPU) for large-scale training and inference. Establish strict testing, rollback, and fail-safe mechanisms for model deployment in live systems. Qualifications Minimum 3 years of focused experience building deep learning systems, with a proven track record in NLP and/or generative AI. Hands-on experience training and deploying transformer-based models (BERT, T5, GPT, LLaMA, etc.)—from scratch or via fine-tuning. Expert-level Python, with production-grade PyTorch skills (Tensor manipulation, gradient debugging, memory profiling, etc.). Demonstrated ability to work with multi-billion parameter models, and deploy them under real-world latency and throughput constraints. Deep understanding of language modeling, embeddings, attention mechanisms, tokenization strategies, and architectural tradeoffs. Ability to read, implement, and extend research papers into robust, testable, and efficient systems. Experience with AI infrastructure at scale, including distributed training, mixed precision, checkpointing, and A100-level GPU scheduling. Familiarity with vector databases (FAISS, Weaviate, Milvus) and hybrid search systems. Proficiency in MLOps tools (MLflow, Airflow, WandB, or similar) for model lifecycle management. Strong commitment to software engineering principles: code quality, version control, CI/CD, and modular design. Capacity to own AI systems end-to-end—from dataset preprocessing to online deployment and continuous improvement. droppGroup is an equal opportunity employer. We offer a competitive compensation structure and a fast-paced growth roadmap to all our teams. Show more Show less

Primary skills:Technology->OpenSystem->Python - OpenSystem Responsible for successful delivery of MLOps solutions and services in client consulting environments; Define key business problems to be solved; formulate high level solution approaches and identify data to solve those problems, develop, analyze/draw conclusions and present to client. Assist clients with operationalization metrics to track performance of ML Models Agile trained to manage team effort and track through JIRA High Impact Communication- Assesses the target audience need, prepares and practices a logical flow, answers audience questions appropriately and sticks to timeline. Technical knowledge- has expertise in cloud technologies, specifically MS Azure, and services with hands on coding to – Expertise in Object Oriented Python Programming with 6 -8 years’ experience. DevOps Working knowledge with implementation experience - 1 or 2 projects a minimum Hands-On MS Azure Cloud knowledge Understand and take requirements on Operationalization of ML Models from Data Scientist Help team with ML Pipelines from creation to execution List Azure services required for deployment, Azure Data bricks and Azure DevOps Setup Assist team to coding standards (flake8 etc) Guide team to debug on issues with pipeline failures Engage with Business / Stakeholders with status update on progress of development and issue fix Automation, Technology and Process Improvement for the deployed projects Setup Standards related to Coding, Pipelines and Documentation Adhere to KPI / SLA for Pipeline Run, Execution Research on new topics, services and enhancements in Cloud Technologies Domain / Technical / Tools Knowledge: Object oriented programming, coding standards, architecture & design patterns, Config management, Package Management, Logging, documentation Experience in Test Driven Development and experience in using Pytest frameworks, git version control, Rest APIs Python programming with OOPs concept, SQL, XML, YAML, Bash, JSON, Pydantic models, Class based frameworks, Dependency injections FastAPI, Flask, Streamlit, Python, Azure API management, API Gateways, Traffic Manager, Load Balancers Nginx, Uvicorn, Gunicorn, Azure ML best practices in environment management, run time configurations (Azure ML & Databricks clusters), alerts. Experience designing and implementing ML Systems & pipelines, MLOps practices and tools such a MLFlow, Kubernetes, etc. Exposure to event driven orchestration, Online Model deployment Contribute towards establishing best practices in MLOps Systems development Proficiency with data analysis tools (e.g., SQL, R & Python) High level understanding of database concepts/reporting & Data Science concepts Hands on experience in working with client IT/Business teams in gathering business requirement and converting into requirement for development team Experience in managing client relationship and developing business cases for opportunities Azure AZ-900 Certification with Azure Architect Good knowledge on software configuration management systems Strong business acumen, strategy and cross-industry thought leadership Awareness of latest technologies and Industry trends Education and Experience: Overall, 6 to 8 years of experience in Data driven software engineering with 3-5 years of experience designing, building and deploying enterprise AI or ML applications with at least 2 years of experience implementing full lifecycle ML automation using MLOps(scalable development to deployment of complex data science workflows) Bachelors or Master’s degree in Computer Science Engineering or equivalent Domain experience in Retail, CPG and Logistics etc. Azure Certified – DP100, AZ/AI900 Logical thinking and problem solving skills along with an ability to collaborate Two or three industry domain knowledge Understanding of the financial processes for various types of projects and the various pricing models available Client Interfacing skills Knowledge of SDLC and agile methodologies Project and Team management Show more Show less

Redefine the future of customer experiences. One conversation at a time. We're changing the game with a first-of-its-kind, conversation-centric platform that unifies team collaboration and customer experience in one place. Powered by AI, built by amazing humans. Our culture is forward-thinking, customer-obsessed and built on an unwavering belief that connection fuels business and life; connections to our customers with our signature Amazing Service®, our products and services, and most importantly, each other. Since 2008, 100,000+ companies and 1M+ users rely on Nextiva for customer and team communication. If you're ready to collaborate and create with amazing people, let your personality shine and be on the frontlines of helping businesses deliver amazing experiences, you're in the right place. Build Amazing - Deliver Amazing - Live Amazing - Be Amazing We are looking for a visionary Head of Engineering (AI & ML) with extensive experience in leading AI/ML initiatives, team leadership, and end-to-end product delivery. This role combines strategic leadership with deep technical expertise to drive the development of advanced AI solutions, such as Agent Assist, IVA, Chatbots, Conversational Intelligence, and Data Visualization. You will work at the intersection of cutting-edge technology and business strategy, managing high-performing teams to deliver scalable, high-value AI products. Key Responsibilities: Strategic Leadership Vision and Strategy: Partner with leadership to define AI product visions, success metrics, and strategic initiatives. Roadmap Development: Shape the medium and long-term AI product roadmap, aligning technical capabilities with business objectives. Emerging Trends: Serve as a thought leader, identifying and championing the adoption of emerging AI/ML trends and technologies. AI Product & Technical Delivery AI/ML Model Development: Oversee the training, fine-tuning, and deployment of advanced AI models, including NLP, ASR, TTS, and generative AI systems. Product Innovation: Drive the design and implementation of core AI/ML features to support intelligent automation and conversational experiences. Resource Management: Strategically plan and allocate team resources to meet roadmap goals and manage dependencies effectively. Scalability: Architect scalable AI systems with high availability, low latency, and adherence to SLAs. Engineering Leadership Technical Guidance: Provide hands-on technical leadership, diving into architecture, code, and design while managing the broader product delivery. Team Performance: Build and sustain an engineering rhythm that fosters high performance, knowledge sharing, and smooth execution. MLOps & Infrastructure: Establish scalable infrastructure and automated pipelines for model training, deployment, and performance monitoring. Team Development and Culture Mentorship: Act as a coach and mentor to foster technical growth and career development for team members. Inclusive Culture: Build a fun, inclusive, and supportive work environment that aligns with company values and encourages collaboration. Exemplify Leadership Principles: Inspire the team by modeling resilience, learning from failures, and celebrating the success of others. Cross-Functional Collaboration Partnerships: Collaborate with product management, design, and business stakeholders to ensure AI solutions meet market and regulatory requirements. Communication: Translate complex technical strategies into clear, actionable insights for both technical and non-technical stakeholders. Required Qualifications: Education: Master's degree in Applied Mathematics, Computer Science, or a related field. Experience: 10+ years in software engineering with expertise in AI/ML. Proven track record in leading teams to deliver AI products such as IVA, chatbots, or conversational intelligence. Hands-on experience with VoIP communications and real-time AI-driven solutions. Strong foundation in end-to-end AI product development and regulatory compliance. Demonstrated ability to evaluate and implement algorithmic solutions tailored to business use cases. Technical Skills: Deep knowledge of NLP, machine learning, and deep learning frameworks (e.g., TensorFlow, PyTorch, Hugging Face). Experience deploying AI systems at scale using Docker, Kubernetes, and cloud platforms (AWS, GCP, Azure). Expertise in optimization techniques like vLLM, quantization, and LoRA for high-performance inferencing. Proficiency in programming languages such as Python and experience building production-grade pipelines. Preferred Skills: MLOps Expertise: Advanced knowledge of CI/CD pipelines, monitoring tools (MLflow, Airflow), and distributed training frameworks. Scalable Training Infrastructure: Hands-on experience with GPU/TPU workloads and frameworks like Horovod or DeepSpeed. Generative AI Expertise: Experience designing Retrieval-Augmented Generation (RAG) systems and fine-tuning large language models for domain-specific applications. Leadership Attributes: Strong people management and mentoring skills with a proven ability to build high-performing teams. Ability to measure team impact, set clear goals, and drive collaboration across functions. Exceptional problem-solving and decision-making skills in ambiguous, high-impact scenarios. If you're passionate about leading the development of transformative AI/ML solutions and want to make an organizational impact through innovative technologies, apply now to join our team! Total Rewards Our Total Rewards offerings are designed to allow our employees to take care of themselves and their families so they can be their best, in and out of the office. Our compensation packages are tailored to each role and candidate's qualifications. We consider a wide range of factors, including skills, experience, training, and certifications, when determining compensation. We aim to offer competitive salaries or wages that reflect the value you bring to our team. Depending on the position, compensation may include base salary and/or hourly wages, incentives, or bonuses. Medical - Medical insurance coverage is available for employees, their spouse, and up to two dependent children with a limit of 500,000 INR, as well as their parents or in-laws for up to 300,000 INR. This comprehensive coverage ensures that essential healthcare needs are met for the entire family unit, providing peace of mind and security in times of medical necessity. Group Term & Group Personal Accident Insurance - Provides insurance coverage against the risk of death / injury during the policy period sustained due to an accident caused by violent, visible & external means. Coverage Type - Employee Only Sum Insured - 3 times of annual CTC with minimum cap of INR 10,00,000 Free Cover Limit - 1.5 Crore Work-Life Balance ️ - 15 days of Privilege leaves per calendar year, 6 days of Paid Sick leave per calendar year, 6 days of Casual leave per calendar year. Paid 26 weeks of Maternity leaves, 1 week of Paternity leave, a day off on your Birthday, and paid holidays Financial Security - Provident Fund & Gratuity Wellness ‍ - Employee Assistance Program and comprehensive wellness initiatives Growth - Access to ongoing learning and development opportunities and career advancement At Nextiva, we're committed to supporting our employees' health, well-being, and professional growth. Join us and build a rewarding career! Established in 2008 and headquartered in Scottsdale, Arizona, Nextiva secured $200M from Goldman Sachs in late 2021, valuing the company at $2.7B.To check out what's going on at Nextiva, check us out on Instagram, Instagram (MX), YouTube, LinkedIn, and the Nextiva blog. #LI-SC1 #LI-Hybrid

WHO YOU ARE: A passionate and skilled Python, AI/ML Lead Engineer with 7+ years of experience. As a Python/AI Lead, you will oversee the development and implementation of machine learning models, AI-driven solutions, and data-driven products. You will guide a team of engineers and collaborate with cross-functional teams to ensure the timely and high-quality delivery of projects. If you thrive in a fast-paced environment and love solving complex problems using data and intelligent algorithms, we'd love to hear from you. WHAT YOU'LL DO: Lead the design, development, and deployment of Gen AI and machine learning solutions using Python. Provide technical guidance and mentorship to team members, ensuring code quality, best practices, and performance optimization. Collaborate with product managers, data scientists, and other stakeholders to define project requirements and objectives. Take ownership of the full software development lifecycle (SDLC), from design to deployment, maintenance, and optimization. Perform code reviews, write technical documentation, and maintain high standards of software quality. Stay up to date with the latest trends and advancements in AI, machine learning, and Python development. Identify and mitigate technical risks in projects while ensuring timely delivery. Foster a collaborative environment and promote knowledge sharing across the engineering team. WHAT YOU'LL NEED: 7+ years of professional experience in Python development, with at least 2 years in a technical leadership role. Strong hands-on experience with AI/ML frameworks, Gen AI LLMs and libraries such as TensorFlow, Scikit-learn, or Keras. Python – Strong hands-on experience. Machine Learning – Practical knowledge of supervised, unsupervised, and deep learning techniques. Generative AI – Experience working with LLMs or similar GenAI technologies. API Development – RESTful APIs and integration of ML models into production services. Databases – Experience with SQL and NoSQL databases (e.g., PostgreSQL, MongoDB, etc.). Good to Have Skills: Cloud Platforms – Familiarity with AWS, Azure, or Google Cloud Platform (GCP). TypeScript/JavaScript – Frontend or full-stack exposure for ML product interfaces. Experience with MLOps tools and practices (e.g., MLflow, Kubeflow, etc.) Exposure to containerization (Docker) and orchestration (Kubernetes) WHAT'S IN IT FOR YOU? At Zinnia, you collaborate with smart, creative professionals who are dedicated to delivering cutting-edge technologies, deeper data insights, and enhanced services to transform how insurance is done. Visit our website at www.zinnia.com for more information. Apply by completing the online application on the careers section of our website. We are an Equal Opportunity employer committed to a diverse workforce. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability

Summary At Novartis, innovation is at the heart of everything we do — and AI is a key enabler in how we reimagine medicine. As an Associate Director Solution Delivery – AI Products, you’ll lead the development and delivery of advanced AI solutions that transform commercial operations in the U.S. market. You will sit at the intersection of technology, data science, and business — owning the product lifecycle from discovery to deployment, while fostering a culture of experimentation, innovation, and continuous delivery. Working within the DD&T Commercial organization, you’ll turn novel ideas into production-ready products that deliver real-world impact. About The Role Key Responsibilities Product Strategy & Innovation Shape and own the product roadmap for AI solutions that power next-gen commercial capabilities — including intelligent targeting, omnichannel orchestration, and HCP engagement optimization. Drive innovation by scouting new AI technologies, validating ideas through MVPs and pilots, and scaling high-value solutions. Translate commercial objectives into actionable technical requirements and solution architectures. Technical Delivery & Solution Ownership Lead cross-functional teams (data science, data engineering, MLOps, digital product) to build, deploy, and operate production-grade AI solutions. Oversee technical delivery from data ingestion and model development to deployment, monitoring, and retraining. Ensure models are performant, scalable, secure, and seamlessly integrated into platforms such as CRM and content engines. Stakeholder Management & Business Alignment Partner with commercial stakeholders (field teams, marketing, analytics) to define needs, align priorities, and drive adoption. Act as a translator between business and technical teams — clearly communicating trade-offs, timelines, and value. Provide thought leadership and influence stakeholders at multiple levels, from working teams to senior leadership. Compliance & Responsible AI Ensure solutions align with Novartis standards and external regulations Embed ethical AI principles into product design — including fairness, transparency, and accountability. Core Technical Focus Areas AI/ML Development: Supervised learning, NLP, recommender systems, experimentation frameworks. Data Infrastructure: Scalable pipelines, real-time data ingestion, structured/unstructured healthcare data. MLOps: Model deployment, versioning, monitoring, and retraining workflows (MLflow, Airflow, SageMaker, etc.). Integration: REST/gRPC APIs, integration with CRM (e.g., Veeva), content platforms, and campaign engines. Cloud Platforms: AWS, Azure, or GCP environments for AI/ML workloads and data operations. What You’ll Bring 5+ years of product management experience, with 2+ years in AI/ML or data-centric product delivery. Strong technical foundation and experience working closely with engineering and data science teams. Demonstrated ability to deliver AI products from concept to production, including service ownership. Strong stakeholder management skills, with the ability to influence across technical and business domains. Experience in healthcare, life sciences, or other regulated environments is a plus. Why Novartis: Helping people with disease and their families takes more than innovative science. It takes a community of smart, passionate people like you. Collaborating, supporting and inspiring each other. Combining to achieve breakthroughs that change patients’ lives. Ready to create a brighter future together? https://www.novartis.com/about/strategy/people-and-culture Join our Novartis Network: Not the right Novartis role for you? Sign up to our talent community to stay connected and learn about suitable career opportunities as soon as they come up: https://talentnetwork.novartis.com/network Benefits and Rewards: Read our handbook to learn about all the ways we’ll help you thrive personally and professionally: https://www.novartis.com/careers/benefits-rewards Show more Show less

We're Hiring: AI DevOps Engineer – ML, LLM & Cloud for Battery & Livestock Intelligence 📍 Hyderabad / Remote | 🧠 3–8 Years Experience 💼 Full-time | Deep Tech | AI-Driven IoT At Vanix Technologies , we’re solving real-world problems using AI built on top of IoT data — from predicting the health of electric vehicle batteries to monitoring livestock behavior with BLE sensors. We’re looking for a hands-on AI DevOps Engineer who understands not just how to build ML/DL models, but also how to turn them into intelligent cloud-native services . If you've worked on battery analytics or sensor-driven ML , and you're excited by the potential of LLMs + real-time IoT — this is for you. What You’ll Work On 🔋 EV Battery Intelligence Build models for SOH, true SOH, SOC, RUL prediction , thermal event detection, and high-risk condition classification. Ingest and process time-series data from BMS, CAN bus, GPS , and environmental sensors. Deliver analytics that plug into our BatteryTelematicsPro SaaS for OEMs and fleet customers. 🐄 Livestock Monitoring AI Analyze BLE sensor data from our cattle wearables (motion, temp, rumination proxies). Develop models for health anomaly detection, estrus prediction, movement patterns , and outlier behaviors. Power actionable insights for farmers via mobile dashboards and alerts. 🤖 Agentic AI & LLM Integration Chain ML outputs with LLMs (e.g., GPT-4, Claude) using LangChain or similar frameworks . Build AI assistants that summarize events, auto-generate alerts, and respond to user queries using both structured and ML-derived data. Support AI-powered explainability and insight generation layers on top of raw telemetry. ☁️ Cloud ML Engineering & DevOps Deploy models on AWS (Lambda, SageMaker, EC2, ECS, CloudWatch). Design and maintain CI/CD pipelines for data, models, and APIs. Optimize performance, cost, and scalability of cloud workloads. ✅ You Must Have Solid foundation in ML/DL for time-series / telemetry data Hands-on with PyTorch / TensorFlow / Scikit-learn / XGBoost Experience with battery analytics or sensor-based animal behavior prediction Understanding of LangChain / OpenAI APIs / LLM orchestration AWS fluency: Lambda, EC2, S3, SageMaker, CloudWatch Python APIs Nice to Have MLOps stack (MLFlow, DVC, W&B) BLE signal processing or CAN bus protocol parsing Prompt engineering or fine-tuning experience Exposure to edge-to-cloud model deployment Why Vanix Technologies? Because we're not another AI lab — we're a deep-tech company building production-ready AI platforms that interact with real devices in the field , used by farmers, OEMs, and EV fleets . You’ll work at the intersection of: IoT + AI + LLMs Hardware + Cloud Mission-critical data + Everyday impact Show more Show less

Required Skills & Qualifications: 4 to 12 years of experience in Data Science, Machine Learning, or AI. Proficiency in Python and libraries like Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch . Experience with ML lifecycle tools such as MLflow, Airflow, or SageMaker. Solid understanding of statistics, probability, and linear algebra . Experience working with structured and unstructured data (SQL, NoSQL, text, images, etc.). Familiarity with cloud platforms like AWS, Azure, or GCP. Strong problem-solving and analytical thinking skills.

Job Summary: We are looking for a highly motivated and analytical Data Scientist / Machine Learning (ML) Engineer / AI Specialist with 1.5 -2 years of experience in Health data analysis, particularly with data sourced from wearable devices such as smartwatches and fitness trackers. The ideal candidate will be proficient in developing data models, analyzing complex datasets, and translating insights into actionable strategies that enhance health-related applications. Key Responsibilities: Develop and implement data models tailored to health data from wearable devices. Stay updated on industry trends and emerging technologies in health data analytics. Ensure data integrity and security throughout the analysis process , correlations relevant to health metrics. Analyze large datasets to extract actionable insights using statistical methods and machine learning techniques. Develop, train, test, and deploy machine learning models for classification, regression, clustering, NLP, recommendation, or computer vision tasks. Collaborate with cross-functional teams including product, engineering, and domain experts to define problems and deliver solutions. Design and build scalable ML pipelines for model development and deployment. Conduct exploratory data analysis (EDA), data wrangling, feature engineering, and model validation. Monitor model performance in production and iterate based on feedback and data drift. Stay up to date with the latest research and trends in machine learning, deep learning, and AI. Document processes, code, and methodologies to ensure reproducibility and collaboration. Required Qualifications: Bachelor's or Master’s degree in Computer Science, Statistics, Mathematics, Engineering, or related field. 1.5-2 years of experience in data analysis, preferably within the health tech sector. Strong knowledge of Python or R and libraries such as NumPy, pandas, scikit-learn, TensorFlow, PyTorch, or XGBoost. Strong experience with data modeling, machine learning algorithms, and statistical analysis. Familiarity with health data privacy regulations (e.g., HIPAA) and data visualization tools (e.g., Tableau, Power BI). Proficiency in SQL and experience working with large-scale data systems (e.g., Spark, Hadoop, BigQuery, Snowflake). Ability to clearly communicate complex technical concepts to both technical and non-technical audiences. Experience with version control tools (e.g., Git) and ML pipeline tools (e.g., MLflow, Airflow, Kubeflow). Experience deploying models in cloud environments (AWS, GCP, Azure). Knowledge of NLP (e.g., Transformers, LLMs), computer vision, or reinforcement learning. Familiarity with MLOps, CI/CD for ML, and model monitoring tools. Experience - 1.5 - 2 years (Only Local Candidates) Location - Mohali Phase 8b Show more Show less

What makes Techjays an inspiring place to work: At Techjays, we are driving the future of artificial intelligence with a bold mission to empower businesses worldwide by helping them build AI solutions that transform industries. As an established leader in the AI space, we combine deep expertise with a collaborative, agile approach to deliver impactful technology that drives meaningful change. Our global team consists of professionals who have honed their skills at leading companies such as Google, Akamai, NetApp, ADP, Cognizant Consulting, and Capgemini. With engineering teams across the globe, we deliver tailored AI software and services to clients ranging from startups to large-scale enterprises. Be part of a company that’s pushing the boundaries of digital transformation. At Techjays, you’ll work on exciting projects that redefine industries, innovate with the latest technologies, and contribute to solutions that make a real-world impact. Join us on our journey to shape the future with AI. We are looking for a mid-level AI Implementation Engineer with a strong Python background to join our AI initiatives team. In this role, you will help design and develop production-ready systems that combine information retrieval, vector databases, and large language models (LLMs) into scalable Retrieval-Augmented Generation (RAG) pipelines. You’ll work closely with AI researchers, backend engineers, and data teams to bring generative AI use cases to life across multiple domains. Key Responsibilities: Develop and maintain scalable Python services that implement AI-powered retrieval and generation workflows. Build and optimize vector-based retrieval pipelines using tools like FAISS , Pinecone , or Weaviate . Integrate LLMs via APIs (e.g., OpenAI, Hugging Face) using orchestration frameworks such as LangChain , LlamaIndex , etc. Collaborate on system architecture, API design, and data flow to support RAG systems. Monitor, test, and improve the performance and accuracy of AI features in production. Work in cross-functional teams with product, data, and ML stakeholders to deploy AI solutions quickly and responsibly. Requirements: 3–5 years of hands-on experience in Python development, with focus on backend or data-intensive systems. Experience with information retrieval concepts and tools (e.g., Elasticsearch, vector search engines). Familiarity with LLM integration or orchestration tools (LangChain, LlamaIndex, etc.). Working knowledge of RESTful API development, microservices, and containerization (Docker). Solid software engineering practices including Git, testing, and CI/CD pipelines. Nice to have: Exposure to prompt engineering or fine-tuning LLMs. Experience deploying cloud-based AI applications (AWS, GCP, or Azure). Familiarity with document ingestion pipelines and unstructured data processing. Understanding of MLOps tools and practices (e.g., MLflow, Airflow). What we offer: Best-in-class packages. Paid holidays and flexible time-off policies. Casual dress code and a flexible working environment. Opportunities for professional development in an engaging, fast-paced environment. Medical insurance covering self and family up to 4 lakhs per person. Diverse and multicultural work environment. Be part of an innovation-driven culture with ample support and resources to succeed. Show more Show less

About Beatly.AI Beatly.AI is a fast-scaling AI startup transforming healthcare through neural network-powered innovation. Our mission is to build clinically meaningful, data-driven solutions that empower medical professionals and enhance patient outcomes. We are seeking an Senior AI/ML Team Engineer to drive both hands-on model development and technical leadership across our deep learning initiatives. About the Role As an Senior AI/ML Team Engineer , you will play a dual role: writing production-grade code, developing and deploying neural network models, while also leading a team of engineers through key initiatives. You’ll be responsible for full-lifecycle development of AI systems—from research and experimentation to scalable cloud deployment—and for shaping our infrastructure and team practices. Key Responsibilities Design and build advanced neural network models (CNNs, LSTMs, GRUs, autoencoders, time-series networks) for real-world healthcare applications. Lead the development of modular, reusable ML pipelines for training, validation, and inference. Actively contribute code and own model architecture, optimization, and deployment workflows. Architect cloud-ready, scalable ML systems using AWS/GCP/Azure, with containers (Docker) and orchestration (Kubernetes). Implement robust ML Ops processes including CI/CD pipelines, model versioning, monitoring, and rollback mechanisms. Collaborate with data, product, and engineering teams to define AI use cases and deliver end-to-end solutions. Guide and mentor a team of engineers—conduct code reviews, help troubleshoot, and support their development. Optimize compute resource usage (e.g., GPU scheduling, mixed precision, parallelism) for large-scale training jobs. Track and improve performance metrics (accuracy, latency, reliability), ensuring production-readiness of deployed models. Evaluate new techniques in neural networks (excluding LLMs) and assess their relevance for healthcare use cases. Skills & Qualifications 4+ years of experience in AI/ML engineering with a strong track record of shipping deep learning solutions. 1+ years of experience in leading or mentoring technical teams, while continuing to build and ship code. Strong proficiency in Python , with hands-on expertise in PyTorch , TensorFlow , or Keras . Deep understanding of neural network architectures for time-series, image, or signal-based tasks. Solid experience deploying models on cloud platforms (AWS/GCP/Azure), using tools like Docker, Kubernetes, and Terraform. Experience with ML pipeline tools (MLFlow, Airflow, DVC, Weights & Biases) and experiment tracking. Proficient in software engineering fundamentals, microservices, API integration, and scalable system design. Excellent written and verbal communication skills with a leadership mindset. Preferred Qualifications Experience with healthcare data: ECG, imaging, vitals, or clinical time-series. Familiarity with HIPAA, FDA, or healthcare compliance workflows. Background in distributed model training and GPU optimisation (e.g., Horovod, TorchElastic). Master’s or PhD in Computer Science, or related discipline. What We Offer Strategic leadership role with deep technical involvement. A mission-driven environment solving problems that matter. Real ownership over architecture, code, and team development. Excellent compensation with top-tier salary . Dynamic, collaborative team culture with space to innovate and grow. Apply Now If you're an experienced deep learning engineer ready to lead and build, and passionate about using neural networks to change the future of healthcare—we want to meet you. Show more Show less

Redefine the future of customer experiences. One conversation at a time. We’re changing the game with a first-of-its-kind, conversation-centric platform that unifies team collaboration and customer experience in one place. Powered by AI, built by amazing humans. Our culture is forward-thinking, customer-obsessed and built on an unwavering belief that connection fuels business and life; connections to our customers with our signature Amazing Service®, our products and services, and most importantly, each other. Since 2008, 100,000+ companies and 1M+ users rely on Nextiva for customer and team communication. If you’re ready to collaborate and create with amazing people, let your personality shine and be on the frontlines of helping businesses deliver amazing experiences, you’re in the right place. Build Amazing - Deliver Amazing - Live Amazing - Be Amazing We are looking for a visionary Head of Engineering (AI & ML) with extensive experience in leading AI/ML initiatives, team leadership, and end-to-end product delivery. This role combines strategic leadership with deep technical expertise to drive the development of advanced AI solutions, such as Agent Assist, IVA, Chatbots, Conversational Intelligence, and Data Visualization. You will work at the intersection of cutting-edge technology and business strategy, managing high-performing teams to deliver scalable, high-value AI products. Key Responsibilities Strategic Leadership Vision and Strategy: Partner with leadership to define AI product visions, success metrics, and strategic initiatives. Roadmap Development: Shape the medium and long-term AI product roadmap, aligning technical capabilities with business objectives. Emerging Trends: Serve as a thought leader, identifying and championing the adoption of emerging AI/ML trends and technologies. AI Product & Technical Delivery AI/ML Model Development: Oversee the training, fine-tuning, and deployment of advanced AI models, including NLP, ASR, TTS, and generative AI systems. Product Innovation: Drive the design and implementation of core AI/ML features to support intelligent automation and conversational experiences. Resource Management: Strategically plan and allocate team resources to meet roadmap goals and manage dependencies effectively. Scalability: Architect scalable AI systems with high availability, low latency, and adherence to SLAs. Engineering Leadership Technical Guidance: Provide hands-on technical leadership, diving into architecture, code, and design while managing the broader product delivery. Team Performance: Build and sustain an engineering rhythm that fosters high performance, knowledge sharing, and smooth execution. MLOps & Infrastructure: Establish scalable infrastructure and automated pipelines for model training, deployment, and performance monitoring. Team Development and Culture Mentorship: Act as a coach and mentor to foster technical growth and career development for team members. Inclusive Culture: Build a fun, inclusive, and supportive work environment that aligns with company values and encourages collaboration. Exemplify Leadership Principles: Inspire the team by modeling resilience, learning from failures, and celebrating the success of others. Cross-Functional Collaboration Partnerships: Collaborate with product management, design, and business stakeholders to ensure AI solutions meet market and regulatory requirements. Communication: Translate complex technical strategies into clear, actionable insights for both technical and non-technical stakeholders. Required Qualifications Education: Master’s degree in Applied Mathematics, Computer Science, or a related field. Experience: 10+ years in software engineering with expertise in AI/ML. Proven track record in leading teams to deliver AI products such as IVA, chatbots, or conversational intelligence. Hands-on experience with VoIP communications and real-time AI-driven solutions. Strong foundation in end-to-end AI product development and regulatory compliance. Demonstrated ability to evaluate and implement algorithmic solutions tailored to business use cases. Technical Skills: Deep knowledge of NLP, machine learning, and deep learning frameworks (e.g., TensorFlow, PyTorch, Hugging Face). Experience deploying AI systems at scale using Docker, Kubernetes, and cloud platforms (AWS, GCP, Azure). Expertise in optimization techniques like vLLM, quantization, and LoRA for high-performance inferencing. Proficiency in programming languages such as Python and experience building production-grade pipelines. Preferred Skills MLOps Expertise: Advanced knowledge of CI/CD pipelines, monitoring tools (MLflow, Airflow), and distributed training frameworks. Scalable Training Infrastructure: Hands-on experience with GPU/TPU workloads and frameworks like Horovod or DeepSpeed. Generative AI Expertise: Experience designing Retrieval-Augmented Generation (RAG) systems and fine-tuning large language models for domain-specific applications. Leadership Attributes Strong people management and mentoring skills with a proven ability to build high-performing teams. Ability to measure team impact, set clear goals, and drive collaboration across functions. Exceptional problem-solving and decision-making skills in ambiguous, high-impact scenarios. If you’re passionate about leading the development of transformative AI/ML solutions and want to make an organizational impact through innovative technologies, apply now to join our team! Total Rewards Our Total Rewards offerings are designed to allow our employees to take care of themselves and their families so they can be their best, in and out of the office. Our compensation packages are tailored to each role and candidate's qualifications. We consider a wide range of factors, including skills, experience, training, and certifications, when determining compensation. We aim to offer competitive salaries or wages that reflect the value you bring to our team. Depending on the position, compensation may include base salary and/or hourly wages, incentives, or bonuses. Medical 🩺 - Medical insurance coverage is available for employees, their spouse, and up to two dependent children with a limit of 500,000 INR, as well as their parents or in-laws for up to 300,000 INR. This comprehensive coverage ensures that essential healthcare needs are met for the entire family unit, providing peace of mind and security in times of medical necessity. Group Term & Group Personal Accident Insurance 💼 - Provides insurance coverage against the risk of death / injury during the policy period sustained due to an accident caused by violent, visible & external means. Coverage Type - Employee Only Sum Insured - 3 times of annual CTC with minimum cap of INR 10,00,000 Free Cover Limit - 1.5 Crore Work-Life Balance ⚖️ - 15 days of Privilege leaves per calendar year, 6 days of Paid Sick leave per calendar year, 6 days of Casual leave per calendar year. Paid 26 weeks of Maternity leaves, 1 week of Paternity leave, a day off on your Birthday, and paid holidays Financial Security💰 - Provident Fund & Gratuity Wellness 🤸‍ - Employee Assistance Program and comprehensive wellness initiatives Growth 🌱 - Access to ongoing learning and development opportunities and career advancement At Nextiva, we're committed to supporting our employees' health, well-being, and professional growth. Join us and build a rewarding career! Established in 2008 and headquartered in Scottsdale, Arizona, Nextiva secured $200M from Goldman Sachs in late 2021, valuing the company at $2.7B.To check out what’s going on at Nextiva, check us out on Instagram, Instagram (MX), YouTube, LinkedIn, and the Nextiva blog. Show more Show less

Redefine the future of customer experiences. One conversation at a time. We’re changing the game with a first-of-its-kind, conversation-centric platform that unifies team collaboration and customer experience in one place. Powered by AI, built by amazing humans. Our culture is forward-thinking, customer-obsessed and built on an unwavering belief that connection fuels business and life; connections to our customers with our signature Amazing Service®, our products and services, and most importantly, each other. Since 2008, 100,000+ companies and 1M+ users rely on Nextiva for customer and team communication. If you’re ready to collaborate and create with amazing people, let your personality shine and be on the frontlines of helping businesses deliver amazing experiences, you’re in the right place. Build Amazing - Deliver Amazing - Live Amazing - Be Amazing We are looking for a visionary Head of Engineering (AI & ML) with extensive experience in leading AI/ML initiatives, team leadership, and end-to-end product delivery. This role combines strategic leadership with deep technical expertise to drive the development of advanced AI solutions, such as Agent Assist, IVA, Chatbots, Conversational Intelligence, and Data Visualization. You will work at the intersection of cutting-edge technology and business strategy, managing high-performing teams to deliver scalable, high-value AI products. Key Responsibilities Strategic Leadership Vision and Strategy: Partner with leadership to define AI product visions, success metrics, and strategic initiatives. Roadmap Development: Shape the medium and long-term AI product roadmap, aligning technical capabilities with business objectives. Emerging Trends: Serve as a thought leader, identifying and championing the adoption of emerging AI/ML trends and technologies. AI Product & Technical Delivery AI/ML Model Development: Oversee the training, fine-tuning, and deployment of advanced AI models, including NLP, ASR, TTS, and generative AI systems. Product Innovation: Drive the design and implementation of core AI/ML features to support intelligent automation and conversational experiences. Resource Management: Strategically plan and allocate team resources to meet roadmap goals and manage dependencies effectively. Scalability: Architect scalable AI systems with high availability, low latency, and adherence to SLAs. Engineering Leadership Technical Guidance: Provide hands-on technical leadership, diving into architecture, code, and design while managing the broader product delivery. Team Performance: Build and sustain an engineering rhythm that fosters high performance, knowledge sharing, and smooth execution. MLOps & Infrastructure: Establish scalable infrastructure and automated pipelines for model training, deployment, and performance monitoring. Team Development and Culture Mentorship: Act as a coach and mentor to foster technical growth and career development for team members. Inclusive Culture: Build a fun, inclusive, and supportive work environment that aligns with company values and encourages collaboration. Exemplify Leadership Principles: Inspire the team by modeling resilience, learning from failures, and celebrating the success of others. Cross-Functional Collaboration Partnerships: Collaborate with product management, design, and business stakeholders to ensure AI solutions meet market and regulatory requirements. Communication: Translate complex technical strategies into clear, actionable insights for both technical and non-technical stakeholders. Required Qualifications Education: Master’s degree in Applied Mathematics, Computer Science, or a related field. Experience: 10+ years in software engineering with expertise in AI/ML. Proven track record in leading teams to deliver AI products such as IVA, chatbots, or conversational intelligence. Hands-on experience with VoIP communications and real-time AI-driven solutions. Strong foundation in end-to-end AI product development and regulatory compliance. Demonstrated ability to evaluate and implement algorithmic solutions tailored to business use cases. Technical Skills: Deep knowledge of NLP, machine learning, and deep learning frameworks (e.g., TensorFlow, PyTorch, Hugging Face). Experience deploying AI systems at scale using Docker, Kubernetes, and cloud platforms (AWS, GCP, Azure). Expertise in optimization techniques like vLLM, quantization, and LoRA for high-performance inferencing. Proficiency in programming languages such as Python and experience building production-grade pipelines. Preferred Skills MLOps Expertise: Advanced knowledge of CI/CD pipelines, monitoring tools (MLflow, Airflow), and distributed training frameworks. Scalable Training Infrastructure: Hands-on experience with GPU/TPU workloads and frameworks like Horovod or DeepSpeed. Generative AI Expertise: Experience designing Retrieval-Augmented Generation (RAG) systems and fine-tuning large language models for domain-specific applications. Leadership Attributes Strong people management and mentoring skills with a proven ability to build high-performing teams. Ability to measure team impact, set clear goals, and drive collaboration across functions. Exceptional problem-solving and decision-making skills in ambiguous, high-impact scenarios. If you’re passionate about leading the development of transformative AI/ML solutions and want to make an organizational impact through innovative technologies, apply now to join our team! Total Rewards Our Total Rewards offerings are designed to allow our employees to take care of themselves and their families so they can be their best, in and out of the office. Our compensation packages are tailored to each role and candidate's qualifications. We consider a wide range of factors, including skills, experience, training, and certifications, when determining compensation. We aim to offer competitive salaries or wages that reflect the value you bring to our team. Depending on the position, compensation may include base salary and/or hourly wages, incentives, or bonuses. Medical 🩺 - Medical insurance coverage is available for employees, their spouse, and up to two dependent children with a limit of 500,000 INR, as well as their parents or in-laws for up to 300,000 INR. This comprehensive coverage ensures that essential healthcare needs are met for the entire family unit, providing peace of mind and security in times of medical necessity. Group Term & Group Personal Accident Insurance 💼 - Provides insurance coverage against the risk of death / injury during the policy period sustained due to an accident caused by violent, visible & external means. Coverage Type - Employee Only Sum Insured - 3 times of annual CTC with minimum cap of INR 10,00,000 Free Cover Limit - 1.5 Crore Work-Life Balance ⚖️ - 15 days of Privilege leaves per calendar year, 6 days of Paid Sick leave per calendar year, 6 days of Casual leave per calendar year. Paid 26 weeks of Maternity leaves, 1 week of Paternity leave, a day off on your Birthday, and paid holidays Financial Security💰 - Provident Fund & Gratuity Wellness 🤸‍ - Employee Assistance Program and comprehensive wellness initiatives Growth 🌱 - Access to ongoing learning and development opportunities and career advancement At Nextiva, we're committed to supporting our employees' health, well-being, and professional growth. Join us and build a rewarding career! Established in 2008 and headquartered in Scottsdale, Arizona, Nextiva secured $200M from Goldman Sachs in late 2021, valuing the company at $2.7B.To check out what’s going on at Nextiva, check us out on Instagram, Instagram (MX), YouTube, LinkedIn, and the Nextiva blog. Show more Show less

Who Are We Looking For We are looking for a Software Engineer II as part of our Enterprise Service Management Engineering team at Nike. The ideal candidate will have strong programming skills with exposure to automation frameworks, API-driven development and familiarity with GenAI and Agentic frameworks. What You Will Work On You’ll be working on designing , developing and running enterprise automation solutions, including but not limited to building workflows, self-service capabilities, and incident deflection systems, to enhance operational efficiency across the enterprise. You will work with a global team of engineers to unlock the potential of data. This will involve collaborating with cross-domain teams of engineers and product managers to integrate systems through API-driven development. You'll have - Bachelor's Engineering degree in Computer Science or similar field of education Minimum 3+ years of experience in software engineering, with a strong focus on programming in either one of the languages Python, Java , NodeJs or GoLang is a must API-Driven Development: Experience in designing, developing, and integrating systems using RESTful APIs and other API-driven approaches is a must DevOps : Proficiency with DevOps tools and practices, including CI/CD pipelines, version control systems (e.g., Git), and infrastructure automation Exposure to ServiceNow Platform : Hands on experience in configuring and building including workflow automation, integrations, and proficiency in any one of its core modules Exposure to Automation Platforms: Hands-on experience with robotic automation platforms such as Automation Anywhere, UiPath, or similar tools is preferred Exposure to implementing and integrating AI, Machine Learning, GenAi and related data solutions language models & tools preferred (i.e. LangChain, Langraph, MLFlow, GPT-4o) Problem-Solving Skills: Strong analytical and troubleshooting skills to resolve complex automation challenges through first principle thinking Collaboration and Communication: Ability to work with cross-functional teams and effectively communicate technical solutions with peers, technical leaders and stakeholders Knowledge of Best Practices: Understanding of industry engineering best practices for automation, security, and scalability Who You Will Work With You will be a part of the Global Technology organization working on Nike’s Enterprise Services Management team reporting to the Software Engineering Manager. You will spend much of your time with Engineers, Product managers and senior technical leadership team in Enterprise Service management team and adjacent teams. Show more Show less

Job Summary JOB DESCRIPTION We are seeking a talented and experienced Data Engineer to join our team. The ideal candidate will be responsible for designing, building, and maintaining scalable data pipelines and systems to support analytics and data-driven decision-making. This role requires expertise in data processing, data modeling, and big data technologies. Responsibilities Key Responsibilities: Design and develop datapipelines to collect, transform, and load data into datalakes and datawarehouses . Optimize ETLworkflows to ensure data accuracy, reliability, and scalability. Collaborate with data analysts, data scientists, and business stakeholders to understand data requirements. Implement and manage cloud − baseddataplatforms (e.g., AWS , Azure , or GoogleCloudPlatform ). Develop datamodels to support analytics and reporting. Monitor and troubleshoot data systems to ensure high performance and minimal downtime. Ensure data quality and security through governance best practices. Document workflows, processes, and architecture to facilitate collaboration and scalability. Stay updated with emerging data engineering technologies and trends. Qualifications Required Skills and Qualifications: Strong proficiency in SQL and Python for data processing and transformation. Hands-on experience with bigdatatechnologies like ApacheSpark , Hadoop , or Kafka . Knowledge of datawarehousingconcepts and tools such as Snowflake , BigQuery , or Redshift . Experience with workfloworchestrationtools like ApacheAirflow or Prefect . Familiarity with cloudplatforms (AWS, Azure, GCP) and their data services. Understanding of datagovernance , security , and compliance best practices. Strong analytical and problem-solving skills. Excellent communication and collaboration abilities. Preferred Qualifications Certification in cloudplatforms (AWS, Azure, or GCP). Experience with NoSQLdatabases like MongoDB , Cassandra , or DynamoDB . Familiarity with DevOpspractices and tools like Docker , Kubernetes , and Terraform . Exposure to machinelearningpipelines and tools like MLflow or Kubeflow . Knowledge of datavisualizationtools like PowerBI , Tableau , or Looker . Show more Show less

hackajob is collaborating with American Express to connect them with exceptional tech professionals for this role. You Lead the Way. We’ve Got Your Back. With the right backing, people and businesses have the power to progress in incredible ways. When you join Team Amex, you become part of a global and diverse community of colleagues with an unwavering commitment to back our customers, communities and each other. Here, you’ll learn and grow as we help you create a career journey that’s unique and meaningful to you with benefits, programs, and flexibility that support you personally and professionally. At American Express, you’ll be recognized for your contributions, leadership, and impact—every colleague has the opportunity to share in the company’s success. Together, we’ll win as a team, striving to uphold our company values and powerful backing promise to provide the world’s best customer experience every day. And we’ll do it with the utmost integrity, and in an environment where everyone is seen, heard and feels like they belong. Join Team Amex and let's lead the way together. How will you make an impact in this role? As part of our Enterprise AI/ML platform engineering team, you can architect, code and ship solutions that makes us an essential part of our customers’ digital lives through AI powered usecases. Here, you can work alongside talented engineers in an open, supportive, inclusive environment where your voice is valued, and you make your own decisions on what tech to use to solve challenging problems in domain of Machine Learning platform. Amex offers a range of opportunities to work with the latest technologies and encourages you to back the broader engineering community through open source. And because we understand the importance of keeping your skills fresh and relevant, we give you dedicated time to invest in your professional development. Find your place in technology on #TeamAmex. Responsibilities Perform technical aspects of software development for assigned applications including design, developing prototypes, and coding assignments. Perform hands-on architecture, design, and development of systems. Drive consistent development practices with respect to tools, common components, and documentation. Spend 80% of time writing code and testing, and remainder of time collaborating with stakeholders through ongoing product/platform releases. Develop deep understanding of tie-ins with other Amex systems and platforms within the supported domains. Perform ongoing refactoring of code, utilize visualization and other techniques to fast-track concepts, and deliver continuous improvement. Identify opportunities to adopt innovative technologies. Provide continuous support for ongoing application availability. Work with product owners to prioritize features for ongoing sprints and managing a list of technical requirements based on industry trends, new technologies, known defects, and issues. Enable business capabilities through innovation. Research and learn new and upcoming technologies, and apply them to develop working software. Debug software components and identify code defects for remediation. Deploy, support, and monitor software across test, integration, and production environments. Automatically scale applications based on demand projections. Influence team members with innovative changes and improvements by challenging status quo and demonstrating risk taking. Demonstrate increased self-reliance to achieve team goals. Minimum Qualifications 2+ years of software development experience with proven hands-on experience building data driven products. Good in Computer Science fundamentals in object-oriented design, data structures, algorithm design, complexity analysis, problem solving and diagnosis Strong analytical and problem-solving skills Adept at any one of the programming language Java/Python and Open to learn new programming languages. Well conversant with Linux / Unix tools Critical Factors to Success (Outcome Driven) Technical/Platforms Experience in large scale platform engineering Experience in application development and integration within one or more Cloud platforms such as Google Cloud Platform, Amazon Web Services, etc. Understanding of Machine Learning Ecosystem with hands on experience working on Airflow, Jupyterlab, Jupyterhub, MLFlow like frameworks. Experience with object-oriented design and coding with Python & related framework. Proficiency on Linux. Understanding and experience with UNIX / Shell scripting Proficiency on distributed systems concepts like load balancing, shards, distributed transactions. Understanding of data structures, algorithms & Design Patterns Good To Have Experience building fast and scalable machine learning and analytical algorithms and executing all tasks from design to deployment and monitoring Experience in developing Web services, micro-services, and REST Experience working with distributed systems using Spark, Hive in Hadoop at significant scale in a production environment. Functional Familiarity with design & coding across multiple platforms & languages Strong analytical & strategic thinking skills Ability to interpret technical /business objectives and challenges Porting/Software Configuration Agile Methodologies Software development/ testing Product Engineering Knowledge Platform engineering knowledge (e.g. Financial Tech/Ecommerce/ Aggregator platforms) Business Outcomes Design and deliver innovative AIML / Big Data platform solutions across multiple business units Identify and adopt new technologies to enhance user experience and predict future challenges Leadership Outcomes Put enterprise thinking first, connect the role's agenda to enterprise priorities and balance the needs of customers, partners, colleagues & shareholders. Lead with an external perspective, challenge status quo and bring continuous innovation to our existing offerings Demonstrate learning agility, make decisions quickly and with the highest level of integrity Lead with a digital mindset and deliver the world's best customer experiences every day Benefits We back you with benefits that support your holistic well-being so you can be and deliver your best. This means caring for you and your loved ones' physical, financial, and mental health, as well as providing the flexibility you need to thrive personally and professionally: Competitive base salaries Bonus incentives Support for financial-well-being and retirement Comprehensive medical, dental, vision, life insurance, and disability benefits (depending on location) Flexible working model with hybrid, onsite or virtual arrangements depending on role and business need Generous paid parental leave policies (depending on your location) Free access to global on-site wellness centers staffed with nurses and doctors (depending on location) Free and confidential counseling support through our Healthy Minds program Career development and training opportunities American Express is an equal opportunity employer and makes employment decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, disability status, age, or any other status protected by law. Offer of employment with American Express is conditioned upon the successful completion of a background verification check, subject to applicable laws and regulations. Show more Show less

Roles and Responsibilities Design, Develop, and Deploy : Develop, deploy, and maintain machine learning models that are not only theoretically sound but also practical and scalable. Our team places a strong emphasis on rapid, trustworthy experimentation for validating models and features. Model Maintenance : Design and build machine learning pipelines optimized for scalability, ensuring seamless model training, evaluation, and deployment. Monitor the performance of machine learning models in real-time using statistical methods, ensuring their efficiency and effectiveness.Implement and manage real-time data systems to handle large data streams efficiently. Technical Expertise : Conduct RD in innovative techniques such as Recommender Systems, Computer Vision, NLP, Generative AI and Causal Inference, pushing the boundaries of practical machine learning applications. Software Development : Develop robust, scalable, and maintainable software solutions for seamless model deployment. CI/CD Pipelines : Set up and manage Continuous Integration/Continuous Deployment (CI/CD) pipelines for automated testing, deployment, and model integration. Collaboration : Work closely with the Product Managers, Platforms and Engineering teams to ensure smooth deployment and integration of ML models into Myntra production systems. Data Management : Utilize big data technologies and data lakes to preprocess and shape raw data for machine learning applications. Code Quality : Write clean, efficient, and maintainable code following best practices. Performance Optimization : Conduct performance testing, troubleshooting, and tuning to ensure optimal model performance. Continuous Learning : Stay up-to-date with the latest advancements in machine learning and technology, sharing insights and knowledge across the organization. Experience Industry Experience: Master's degree in a related technical field with 4+ years of relevant industry experience or Bachelor's degree in Computer Science, Data Science, Machine Learning, Statistics, or a related technical field with 6+ years of relevant industry experience OR OR Ph.D. in a related field with a thesis in a domain relevant to Myntra's needs (e.g., Recommender Systems, Natural Language Processing). Machine Learning Expertise: At least 4 years of hands-on experience as a Machine Learning Engineer or a similar role. Solid understanding of statistics, particularly as it applies to machine learning, including probability theory, hypothesis testing, and statistical inference. Production Deployment: Proven track record of implementing and scaling machine learning models and pipelines in a production environment. Programming Skills: Strong proficiency in Python or equivalent programming languages for model development. ML Frameworks: Familiarity with leading machine learning frameworks (Keras, TensorFlow, PyTorch) and libraries (scikit-learn). CI/CD Tools: Experience with CI/CD tools and practices. Communication: Excellent verbal and written communication skills. Teamwork Independence: Ability to work collaboratively in a team environment or independently as needed. Mentor team members technically on designing and deploying ML pipelines and services. Workload Management: Strong organizational skills to manage and prioritize tasks, supporting your manager effectively. Preferred Qualifications Strong emphasis on rapid, trustworthy experimentation for validating machine learning models and hypotheses. Hands-on experience with Search and Recommender Systems, Computer Vision, or Forecasting is strongly desired. We value candidates who emphasize practical implementation and scaling of machine learning solutions. Experience with real-time systems and databases like Kafka, Cassandra, Vector Databases, or Bigtable is highly valued. Prior experience with Generative AI techniques earns brownie points. Advanced understanding and experience in Causal Inference earns a lot of brownie points. Strong communication skills, especially in conveying complex technical and statistical concepts to a non-technical audience. Experience with big data technologies like Spark or other distributed computing frameworks. Exceptional candidates are encouraged to apply, even if you don't meet every listed qualification. We're open to hiring individuals who demonstrate outstanding potential. Nice to Have Research Contributions: Publications or presentations in recognized Machine Learning and Data Science journals/conferences. Cloud Services: Proficiency in cloud platforms (AWS, Google Cloud) and an understanding of distributed systems. Generative AI Exposure: Familiarity with Generative AI models. Database Management: Experience with SQL and/or NoSQL databases. ML Orchestration: Knowledge of ML orchestration tools (Airflow, Kubeflow, MLFlow).

Halo believes in innovation by inclusion to solve digital problems . As an international agency of over 200 people specializing in interactive media strategy and development, we embrace equity and empowerment in a serious way. Our interdisciplinary teams of unique designers, developers and entrepreneurial minds with a variety of backgrounds, viewpoints, and skills connect to solve business challenges of every shape and size. We empathize to form deep, meaningful relationships with our clients so they can do the same with their audience. Working at Halo feels like belonging . Learn more about our philosophy, benefits, and team at https://halopowered.com/As an AI Architect, you will lead the design of scalable, secure, and modern technology solutions, leveraging artificial intelligence, cloud platforms, and microservices—while ensuring alignment with AI governance principles, agile delivery, and platform modernization strategies As a Data Scientist, you'll be part of a multidisciplinary team applying advanced analytics, machine learning, and generative AI to solve real-world problems across our consulting, health, wealth, and career businesses. You will collaborate closely with engineering, product, and business stakeholders to develop scalable models, design intelligent pipelines, and influence data-driven decision-making across the enterprise. Requirements Design, develop, and deploy robust machine learning models and data pipelines that support AI-enabled applications Apply exploratory data analysis (EDA) and feature engineering techniques to extract insights and improve model performance Collaborate with cross-functional teams to translate business problems into analytical use cases Contribute to the full machine learning lifecycle: from data preparation and model experimentation to deployment and monitoring Work with structured and unstructured data, including text, to develop NLP and generative AI solutions Define and enforce best practices in model validation, reproducibility, documentation, and versioning Partner with engineering to integrate models into production systems using CI/CD pipelines and cloud-native services Stay current with industry trends, emerging techniques (e.g., RAG, LLMs, embeddings), and relevant tools Required Skills & Qualifications 3+ years of experience in Data Science, Machine Learning, or Applied AI roles Proficiency in Python (preferred) and a strong grasp of pandas, NumPy, and scikit-learn Skilled in data querying, manipulation, and pipeline development using SQL and modern ETL frameworks Experience working with Databricks, including notebooks, MLflow, Delta Lake, and job orchestration Experience with Git-based workflows and Agile methodologies Strong analytical thinking, problem-solving skills, and communication abilities Exposure to Generative AI, LLMs, prompt engineering, or vector-based search Hands-on experience with cloud platforms (AWS, Azure, or GCP) and deploying models in scalable environments Knowledge of data versioning, model registry, and ML lifecycle tools (e.g., MLflow, DVC, SageMaker, DataBricks, or Vertex AI) Experience working with visualization tools like Tableau, Power BI, or Qlik Degree in Computer Science, Data Science, Applied Mathematics, or a related field Benefits 100% RemoteWork Salary in USD Get to work on challenging projects for the U.S Show more Show less

About Vois VO IS (Vodafone Intelligent Solutions) is a strategic arm of Vodafone Group Plc, creating value and enhancing quality and efficiency across 28 countries, and operating from 7 locations: Albania, Egypt, Hungary, India, Romania, Spain and the UK. Over 29,000 highly skilled individuals are dedicated to being Vodafone Group’s partner of choice for talent, technology, and transformation. We deliver the best services across IT, Business Intelligence Services, Customer Operations, Business Operations, HR, Finance, Supply Chain, HR Operations, and many more. Established in 2006, VO IS has evolved into a global, multi-functional organisation, a Centre of Excellence for Intelligent Solutions focused on adding value and delivering business outcomes for Vodafone. About VOIS India In 2009, VO IS started operating in India and now has established global delivery centres in Pune, Bangalore and Ahmedabad. With more than 14,500 employees, VO IS India supports global markets and group functions of Vodafone, and delivers best-in-class customer experience through multi-functional services in the areas of Information Technology, Networks, Business Intelligence and Analytics, Digital Business Solutions (Robotics & AI), Commercial Operations (Consumer & Business), Intelligent Operations, Finance Operations, Supply Chain Operations and HR Operations and more. Job Description Key responsibilities include: GCP certifications (e.g., Professional Cloud DevOps Engineer, Cloud Architect). Experience deploying and managing AI/ML and GenAI models in production. Familiarity with data governance, model lifecycle management, and responsible AI practices. Cloud Expertise: Deep experience with Google Cloud Platform (GCP) services (Compute Engine, GKE, Cloud Functions, Vertex AI, BigQuery, etc.). DevOps Tools: Jenkins, GitLab CI/CD, ArgoCD, or similar. IaC: Terraform, Google Deployment Manager, Ansible. Containers & Orchestration: Docker, Kubernetes (GKE preferred), Helm. Monitoring & Logging: Google Cloud Operations Suite (formerly Stackdriver), Prometheus. Scripting & Automation: Python, Bash, NodeJs. AI/ML & GenAI: Experience with Vertex AI, Kubeflow, MLflow, LangChain, Hugging Face, or OpenAI APIs. Security & Compliance: IAM, VPC, service accounts, secrets management. Experience 12+ years of experience in DevOps/cloud roles, with 3+ years in a leadership capacity. Must Have Technical / Professional Qualifications Bachelor’s or Master’s degree in Computer Science, Engineering, or related field. DevOps Tools: Jenkins, GitLab CI/CD, ArgoCD, or similar. VOIS Equal Opportunity Employer Commitment India VO IS is proud to be an Equal Employment Opportunity Employer. We celebrate differences and we welcome and value diverse people and insights. We believe that being authentically human and inclusive powers our employees’ growth and enables them to create a positive impact on themselves and society. We do not discriminate based on age, colour, gender (including pregnancy, childbirth, or related medical conditions), gender identity, gender expression, national origin, race, religion, sexual orientation, status as an individual with a disability, or other applicable legally protected characteristics. As a result of living and breathing our commitment, our employees have helped us get certified as a Great Place to Work in India for four years running. We have been also highlighted among the Top 10 Best Workplaces for Millennials, Equity, and Inclusion , Top 50 Best Workplaces for Women , Top 25 Best Workplaces in IT & IT-BPM and 10th Overall Best Workplaces in India by the Great Place to Work Institute in 2024. These achievements position us among a select group of trustworthy and high-performing companies which put their employees at the heart of everything they do. By joining us, you are part of our commitment. We look forward to welcoming you into our family which represents a variety of cultures, backgrounds, perspectives, and skills! Apply now, and we’ll be in touch! Show more Show less