1795 Mlflow Jobs - Page 3

As a Senior Machine Learning Engineer with over 10 years of experience, you will play a crucial role in designing, building, and deploying scalable machine learning systems in production. In this role, you will collaborate closely with data scientists to operationalize models, take ownership of ML pipelines from end to end, and enhance the reliability, automation, and performance of our ML infrastructure. Your primary responsibilities will include designing and constructing robust ML pipelines and services for training, validation, and model deployment. You will work in collaboration with various stakeholders such as data scientists, solution architects, and DevOps engineers to ensure alignment with project goals and requirements. Additionally, you will be responsible for ensuring cloud integration compatibility with AWS and Azure, building reusable infrastructure components following best practices in DevOps and MLOps, and adhering to security standards and regulatory compliance. To excel in this role, you should possess strong programming skills in Python, have deep experience with ML frameworks such as TensorFlow, PyTorch, and Scikit-learn, and be proficient in MLOps tools like MLflow, Airflow, TFX, Kubeflow, or BentoML. Experience in deploying models using Docker and Kubernetes, familiarity with cloud platforms and ML services, and proficiency in data engineering tools are essential for success in this position. Additionally, knowledge of CI/CD, version control, and infrastructure as code along with experience in monitoring/logging tools will be advantageous. Good-to-have skills include experience with feature stores and experiment tracking platforms, knowledge of edge/embedded ML, model quantization, and optimization, as well as familiarity with model governance, security, and compliance in ML systems. Exposure to on-device ML or streaming ML use cases and experience in leading cross-functional initiatives or mentoring junior engineers will also be beneficial. Joining Ericsson will provide you with an exceptional opportunity to leverage your skills and creativity to address some of the world's toughest challenges. You will be part of a diverse team of innovators who are committed to pushing the boundaries of innovation and crafting groundbreaking solutions. As a member of this team, you will be challenged to think beyond conventional limits and contribute to shaping the future of technology.,

You should have at least 2-7 years of experience in software engineering and ML development. Proficiency in Python and ML libraries like Scikit-learn, TensorFlow, or PyTorch is essential. Your responsibilities will include building and evaluating models, data preprocessing, and feature engineering. It is important to have a good understanding of REST APIs, Docker, Git, and CI/CD tools. A strong foundation in software engineering principles such as data structures, algorithms, and design patterns is required. Hands-on experience with MLOps platforms like MLflow, TFX, Airflow, and Kubeflow is preferred. Exposure to NLP, large language models (LLMs), or computer vision projects will be beneficial for this role. Experience with cloud platforms such as AWS, GCP, and Azure, as well as managed ML services, is a plus. Any contributions to open-source ML libraries or participation in ML competitions like Kaggle or DrivenData will be considered an advantage.,

You will be joining a technology-driven publishing and legal-tech organization that is currently enhancing its capabilities through advanced AI initiatives. As an experienced AI Solution Architect, your role will involve leading the design, development, and deployment of transformative AI projects. You will work closely with a proficient internal team skilled in .NET, MERN, MEAN stacks, and recent chatbot development using OpenAI and LLaMA. Your responsibilities will include architecting, planning, and delivering enterprise-grade AI solutions utilizing Vector Databases like FAISS and Chroma, RAG Pipelines (Retrieval-Augmented Generation), and LLM techniques such as Pre-training, Fine-tuning, and RLHF (Reinforcement Learning with Human Feedback). You will lead AI solution design discussions, collaborate with engineering teams to integrate AI modules into systems, and guide junior AI engineers and developers on technical aspects. To excel in this role, you should hold a Bachelors or Masters in Computer Science, Engineering, AI/ML, or related fields and have at least 5 years of experience in software architecture with a focus on AI/ML system design and project delivery. Hands-on expertise in Vector Search Engines, LLM Tuning & Deployment, RAG systems, RLHF techniques, and working with multi-tech teams is essential. Strong command over architecture principles, scalability, microservices, API-based integration, and excellent team leadership skills are also required. It would be advantageous if you have experience with tools like MLflow, Weights & Biases, Docker, Kubernetes, Azure/AWS AI services, exposure to data pipelines, MLOps, AI governance, familiarity with enterprise software lifecycle, and DevSecOps practices. Prior experience in delivering a production-grade AI/NLP project with measurable impact is a plus. Stay updated on emerging AI trends and assess their relevance to business objectives to drive AI adoption across products and internal processes.,

As an AI / ML Engineer, you will be responsible for utilizing your expertise in the field of Artificial Intelligence and Machine Learning to develop innovative solutions. You should hold a Bachelor's or Master's degree in Computer Science, Engineering, Data Science, AI/ML, Mathematics, or a related field. With a minimum of 6 years of experience in AI/ML, you are expected to demonstrate proficiency in Python and various ML libraries such as scikit-learn, XGBoost, pandas, NumPy, matplotlib, and seaborn. In this role, you will need a strong understanding of machine learning algorithms and deep learning architectures including CNNs, RNNs, and Transformers. Hands-on experience with TensorFlow, PyTorch, or Keras is essential. You should also have expertise in data preprocessing, feature selection, exploratory data analysis (EDA), and model interpretability. Additionally, familiarity with API development and deploying models using frameworks like Flask, FastAPI, or similar tools is required. Experience with MLOps tools such as MLflow, Kubeflow, DVC, and Airflow will be beneficial. Knowledge of cloud platforms like AWS (SageMaker, S3, Lambda), GCP (Vertex AI), or Azure ML is preferred. Proficiency in version control using Git, CI/CD processes, and containerization with Docker is essential for this role. Bonus skills that would be advantageous include familiarity with NLP frameworks (e.g., spaCy, NLTK, Hugging Face Transformers), Computer Vision experience using OpenCV or YOLO/Detectron, and knowledge of Reinforcement Learning or Generative AI (GANs, LLMs). Experience with vector databases such as Pinecone or Weaviate, as well as LangChain for AI agent building, is a plus. Familiarity with data labeling platforms and annotation workflows will also be beneficial. In addition to technical skills, you should possess soft skills such as an analytical mindset, strong problem-solving abilities, effective communication, and collaboration skills. The ability to work independently in a fast-paced, agile environment is crucial. A passion for AI/ML and a proactive approach to staying updated with the latest developments in the field are highly desirable for this role.,

You will be working as an AI Platform Engineer in Bangalore as part of the GenAI COE Team. Your key responsibilities will involve developing and promoting scalable AI platforms for customer-facing applications. It will be essential to evangelize the platform with customers and internal stakeholders, ensuring scalability, reliability, and performance to meet business needs. Your role will also entail designing machine learning pipelines for experiment management, model management, feature management, and model retraining. Implementing A/B testing of models and designing APIs for model inferencing at scale will be crucial. You should have proven expertise with MLflow, SageMaker, Vertex AI, and Azure AI. As an AI Platform Engineer, you will serve as a subject matter expert in LLM serving paradigms, with in-depth knowledge of GPU architectures. Expertise in distributed training and serving of large language models, along with proficiency in model and data parallel training using frameworks like DeepSpeed and service frameworks like vLLM, will be required. Demonstrating proven expertise in model fine-tuning and optimization techniques to achieve better latencies and accuracies in model results will be part of your responsibilities. Reducing training and resource requirements for fine-tuning LLM and LVM models will also be essential. Having extensive knowledge of different LLM models and providing insights on their applicability based on use cases is crucial. You should have proven experience in delivering end-to-end solutions from engineering to production for specific customer use cases. Your proficiency in DevOps and LLMOps practices, along with knowledge of Kubernetes, Docker, and container orchestration, will be necessary. A deep understanding of LLM orchestration frameworks such as Flowise, Langflow, and Langgraph is also required. In terms of skills, you should be familiar with LLM models like Hugging Face OSS LLMs, GPT, Gemini, Claude, Mixtral, and Llama, as well as LLM Ops tools like ML Flow, Langchain, Langraph, LangFlow, Flowise, LLamaIndex, SageMaker, AWS Bedrock, Vertex AI, and Azure AI. Additionally, knowledge of databases/data warehouse systems like DynamoDB, Cosmos, MongoDB, RDS, MySQL, PostGreSQL, Aurora, and Google BigQuery, as well as cloud platforms such as AWS, Azure, and GCP, is essential. Proficiency in DevOps tools like Kubernetes, Docker, FluentD, Kibana, Grafana, and Prometheus, along with cloud certifications like AWS Professional Solution Architect and Azure Solutions Architect Expert, will be beneficial. Strong programming skills in Python, SQL, and Javascript are required for this full-time role, with an in-person work location.,

???? About Es Magico Es Magico is an AI-first enterprise transformation organisation that goes beyond consulting we deliver scalable execution across sectors such as BFSI, Healthcare, Entertainment, and Education. With offices in Mumbai and Bengaluru, our mission is to augment the human workforce by deploying bespoke AI employees across business functions, innovating swiftly and executing with trust. We also partner with early-stage startups as a venture builder, transforming 0 ? 1 ideas into AI-native, scalable products. ???? Role: MLOps Engineer ??? Location: Bengaluru (Hybrid) ??? Experience: 14 years ??? Joining: Immediate ???? Key Responsibilities Design, develop, and maintain scalable ML pipelines for training, testing, and deployment. Automate model deployment, monitoring, and version control across dev/staging/prod environments. Integrate CI/CD pipelines for ML models using tools like MLflow, Kubeflow, Airflow, etc. Manage containerized workloads using Docker and orchestrate with Kubernetes or GKE. Collaborate closely with data scientists and product teams to optimize ML model lifecycle. Monitor performance and reliability of deployed models and troubleshoot issues as needed. ????? Technical Skills Experience with MLOps frameworks: MLflow, TFX, Kubeflow, or SageMaker Pipelines. Proficient in Python and common ML libraries (scikit-learn, pandas, etc.). Solid understanding of CI/CD practices and tools (e.g., GitHub Actions, Jenkins, Cloud Build). Familiar with Docker, Kubernetes, and Google Cloud Platform (GCP). Comfortable with data pipeline tools like Airflow, Prefect, or equivalent. ???? Preferred Qualifications 14 years of experience in MLOps, ML engineering, or DevOps with ML workflows. Prior experience with model monitoring, drift detection, and automated retraining. Exposure to data versioning tools like DVC or Delta Lake is a plus. GCP certifications or working knowledge of Vertex AI is a strong advantage. ???? How to Apply Send your resume to [HIDDEN TEXT] with the subject line: Application MLOps Engineer. Show more Show less

???? Were Hiring: AI Engineer ???? Location: Bengaluru (Regular office-based role) ???? Employment Type: Full-Time | 5 Days a Week from Office ???? Qualification: B.E / B.Tech or equivalent degree in Computer Science, IT, or related field Are you passionate about building and scaling production-grade AI/ML systems We&aposre looking for a skilled AI Engineer to join our team in Bengaluru and help drive real-world impact through cutting-edge machine learning and GenAI technologies. ???? Must-Have Skills: 48 years of hands-on experience in designing, building, and deploying production-grade AI/ML solutions Proficiency in Python, PySpark, SQL , and ML libraries like Scikit-learn, XGBoost, LightGBM Cloud-native ML development experience on AWS (SageMaker), GCP (Vertex AI), or Azure ML Strong background in NLP/GenAI frameworks: Hugging Face, LangChain, LlamaIndex Practical knowledge of MLOps tools (MLflow, Weights & Biases, DVC) and deployment frameworks ( FastAPI, Flask, Docker, Kubernetes ) Excellent communication, stakeholder engagement, and team collaboration skills Good-to-Have: Publications, blog posts, or open-source contributions in AI/ML Experience leading AI strategy or owning technical roadmaps Show more Show less

About Biz2X Biz2X is the leading digital lending platform, enabling financial providers to power growth with a modern omni-channel experience, best-in-class risk management tools and a comprehensive yet flexible Servicing engine. The company partners with financial institutions to support their Digital Transformation efforts with Biz2Xs digital lending platform. Biz2X solutions not only reduces operational expenses, but accelerates lending growth by significantly improving client experience, reducing total turnaround time, and equipping the relationship managers with powerful monitoring insights and alerts Read Our Latest Press Release : Press Release - Biz 2X Job Overvi ew: We are seeking for a Senior Engineer AI/ML to drive the development and deployment of sophisticated AI solutions in our fintech products. You will oversee MLOps pipelines and manage large language models (LLMs) to enhance our financial technology services. Key Responsibilities: AI/ML Development: Design and implement advanced ML models for applications including fraud detection, credit scoring, and algorithmic trading. MLOps: Develop and manage MLOps pipelines using tools such as MLflow, Kubeflow, and Airflow for CI/CD, model monitoring, and automation. LLMOps: Optimize and operationalize LLMs (e.g., GPT-4, BERT) for fintech applications like automated customer support and sentiment analysis. Collaboration: Work with product managers, data engineers, and business analysts to align technical solutions with business objectives. Qualifications: Experience: 4-6 years in AI, ML, MLOps, and LLMOps with a focus on fintech. Technical Skills: Expertise in TensorFlow, PyTorch, scikit-learn, and MLOps tools (MLflow, Kubeflow). Proficiency in large language models (LLMs) and cloud platforms (AWS, GCP, Azure). Strong programming skills in Python, Java, or Scala. Experience in building RAG pipelines, NLP, OCR and Pyspark Good to have: Production GenAI Experience in Fintech/Lending domain Show more Show less

Job Title: AI Research Engineer Intern (Fresher) Reporting to: Lead Research & Innovation Lab Location: remote/ Hybrid (Chennai, India) Engagement: 6-month, full-time paid internship with pre-placement-offer track 1. Why this role exists Stratsyn AI Technology Services is turbo-charging Stratsyns cloud-native Enterprise Intelligence & Management Suite a modular SaaS ecosystem that fuses advanced AI, low-code automation, multimodal search, and next-generation Virtual workforce agents. The platform unifies strategic planning, document intelligence, workflow orchestration, and real-time analytics, empowering C-suite leaders to simulate scenarios, orchestrate execution, and convert insight into action with unmatched speed and scalability. To keep pushing that frontier, we need sharp, curious minds who can translate cutting-edge research into production-grade capabilities for this suite. This internship is our talent-funnel into future Research Engineer and Product Scientist roles. 2. What youll do (core responsibilities) % FocusKey Responsibility 30 %Rapid Prototyping & Experimentation implement state-of-the-art papers (LLMs, graph learning, causal inference, agents), design ablation studies, benchmark against baselines, and iterate fast. 25 %Data Engineering for Research build reproducible datasets, craft synthetic data when needed, automate ETL pipelines, and enforce experiment tracking (MLflow / Weights & Biases). 20 %Model Evaluation & Explainability create evaluation harnesses (BLEU, ROUGE, MAPE, custom KPIs), visualize error landscapes, and generate executive-ready insights. 15 %Collaboration & Documentation author tech memos, well-annotated notebooks, and contribute to internal knowledge bases; present findings in weekly research stand-ups. 10 %Innovation Scouting scan arXiv, ACL, NeurIPS, ICML, and startup ecosystems; summarize high-impact research and propose areas for IP creation within the Suite. 3. What you will learn / outcomes to achieve Master the end-to-end research workflow: literature review ? hypothesis ? prototype ? validation ? deployment shadow. Deliver one peer-review-quality technical report and two production-grade proof-of-concepts for the Suite. Achieve a measurable impact (e.g., 8-10 % forecasting-accuracy lift or 30 % latency reduction) on a live micro-service. 4. Minimum qualifications (freshers welcome) B.E./B.Tech/M.Sc./M.Tech in CS, Data Science, Statistics, EE, or related (2024-2026 pass-out). Fluency in Python and at least one deep-learning framework (PyTorch preferred). Solid grasp of linear algebra, probability, optimization, and algorithms. Hands-on academic or personal projects in NLP, CV, time-series, or RL (GitHub links highly valued). 5. Preferred extras Publications or Kaggle/ML-competition record. Experience with distributed training (GPU clusters, Ray, Lightning) and experiment-tracking tools. Familiarity with MLOps (Docker, CI/CD, Kubernetes) or data-centric AI. Domain knowledge in supply-chain, fintech, climate, or marketing analytics. 6. Key attributes & soft skills First-principles thinker questions assumptions, proposes novel solutions. Bias for action prototypes in hours, not weeks; embraces agile experimentation. Storytelling ability explains complex models in clear, executive-friendly language. Ownership mentality treats the prototype as a product, not just a demo. 7. Tech stack youll touch Python | PyTorch | Hugging Face | TensorRT | LangChain | Neo4j/GraphDB | PostgreSQL | Airflow | MLflow | Weights & Biases | Docker | GitHub Actions | JAX (exploratory) 8. Internship logistics & perks Competitive monthly stipend + performance bonus. High-end workstation + GPU credits on our private cloud. Dedicated mentor and 30-60-90-day learning plan. Access to premium research portals and paid conference passes. Culture of radical candor, weekly brown-bag tech talks, and hack days. Fast-track to full-time AI Research Engineer upon successful completion. 9. Application process Apply via email: Send rsum, brief statement of purpose, and GitHub/portfolio links to [HIDDEN TEXT] . Online coding assessment: algorithmic + ML fundamentals. Technical interview (2 rounds): deep dive into projects, math, and research reasoning. Culture-fit discussion: with Research Lead & CPO. Offer & onboarding target turnaround < 3 weeks. Show more Show less

About the Role: We are seeking an experienced MLOps Engineer to lead the deployment, scaling, and performance optimization of open-source Generative AI models on cloud infrastructure. Youll work at the intersection of machine learning, DevOps, and cloud engineering to help productize and operationalize large-scale LLM and diffusion models. Key Responsibilities: Design and implement scalable deployment pipelines for open-source Gen AI models (LLMs, diffusion models, etc.). Fine-tune and optimize models using techniques like LoRA, quantization, distillation, etc. Manage inference workloads, latency optimization, and GPU utilization. Build CI/CD pipelines for model training, validation, and deployment. Integrate observability, logging, and alerting for model and infrastructure monitoring. Automate resource provisioning using Terraform, Helm, or similar tools on GCP/AWS/Azure. Ensure model versioning, reproducibility, and rollback using tools like MLflow, DVC, or Weights & Biases. Collaborate with data scientists, backend engineers, and DevOps teams to ensure smooth production rollouts. Required Skills & Qualifications: 5+ years of total experience in software engineering or cloud infrastructure. 3+ years in MLOps with direct experience in deploying large Gen AI models. Hands-on experience with open-source models (e.g., LLaMA, Mistral, Stable Diffusion, Falcon, etc.). Strong knowledge of Docker, Kubernetes, and cloud compute orchestration. Proficiency in Python and familiarity with model-serving frameworks (e.g., FastAPI, Triton Inference Server, Hugging Face Accelerate, vLLM). Experience with cloud platforms (GCP preferred, AWS or Azure acceptable). Familiarity with distributed training, checkpointing, and model parallelism. Good to Have: Experience with low-latency inference systems and token streaming architectures. Familiarity with cost optimization and scaling strategies for GPU-based workloads. Exposure to LLMOps tools (LangChain, BentoML, Ray Serve, etc.). Why Join Us: Opportunity to work on cutting-edge Gen AI applications across industries. Collaborative team with deep expertise in AI, cloud, and enterprise software. Flexible work environment with a focus on innovation and impact. Show more Show less

Comcast brings together the best in media and technology. We drive innovation to create the world's best entertainment and online experiences. As a Fortune 50 leader, we set the pace in a variety of innovative and fascinating businesses and create career opportunities across a wide range of locations and disciplines. We are at the forefront of change and move at an amazing pace, thanks to our remarkable people, who bring cutting-edge products and services to life for millions of customers every day. If you share in our passion for teamwork, our vision to revolutionize industries and our goal to lead the future in media and technology, we want you to fast-forward your career at Comcast. Job Summary Responsible for developing and deploying machine learning algorithms. Evaluates accuracy and functionality of machine learning algorithms. Translates application requirements into machine learning problem statements. Analyzes and evaluates solutions both internally generated as well as third party supplied. Develops novel ways to use machine learning to solve problems and discover new products. Has in-depth experience, knowledge and skills in own discipline. Usually determines own work priorities. Acts as resource for colleagues with less experience. Job Description About the Role: We are seeking an experienced Data Scientist to join our growing Operational Intelligence team. You will play a key role in building intelligent systems that help reduce alert noise, detect anomalies, correlate events, and proactively surface operational insights across our large-scale streaming infrastructure. You’ll work at the intersection of machine learning, observability, and IT operations, collaborating closely with Platform Engineers, SREs, Incident Managers, Operators and Developers to integrate smart detection and decision logic directly into our operational workflows. This role offers a unique opportunity to push the boundaries of AI/ML in large-scale operations. We welcome curious minds who want to stay ahead of the curve, bring innovative ideas to life, and improve the reliability of streaming infrastructure that powers millions of users globally. What You’ll Do Design and tune machine learning models for event correlation, anomaly detection, alert scoring, and root cause inference Engineer features to enrich alerts using service relationships, business context, change history, and topological data Apply NLP and ML techniques to classify and structure logs and unstructured alert messages Develop and maintain real-time and batch data pipelines to process alerts, metrics, traces, and logs Use Python, SQL, and time-series query languages (e.g., PromQL) to manipulate and analyze operational data Collaborate with engineering teams to deploy models via API integrations, automate workflows, and ensure production readiness Contribute to the development of self-healing automation, diagnostics, and ML-powered decision triggers Design and validate entropy-based prioritization models to reduce alert fatigue and elevate critical signals Conduct A/B testing, offline validation, and live performance monitoring of ML models Build and share clear dashboards, visualizations, and reporting views to support SREs, engineers and leadership Participate in incident postmortems, providing ML-driven insights and recommendations for platform improvements Collaborate on the design of hybrid ML + rule-based systems to supportnamic correlation and intelligent alert grouping Lead and support innovation efforts including POCs, POVs, and explorationemerging AI/ML tools and strategies Demonstrate a proactive, solution-oriented mindset with the ability to navigate ambiguity and learn quickly Participate in on-call rotations and provide operational support as needed Qualifications Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, Statistics or a related field 5+ years of experience building and deploying ML solutions in production environments 2+ years working with AIOps, observability, or real-time operations data Strong coding skills in Python (including pandas, NumPy, Scikit-learn, PyTorch, or TensorFlow) Experience working with SQL, time-series query languages (e.g., PromQL), and data transformation in pandas or Spark Familiarity with LLMs, prompt engineering fundamentals, or embedding-based retrieval (e.g., sentence-transformers, vector DBs) Strong grasp of modern ML techniques including gradient boosting (XGBoost/LightGBM), autoencoders, clustering (e.g., HDBSCAN), and anomaly detection Experience managing structured + unstructured data, and building features from logs, alerts, metrics, and traces Familiarity with real-time event processing using tools like Kafka, Kinesis, or Flink Strong understanding of model evaluation techniques including precision/recall trade-offs, ROC, AUC, calibration Comfortable working with relational (PostgreSQL), NoSQL (MongoDB), and time-series (InfluxDB, Prometheus) databases Ability to collaborate effectively with SREs, platform teams, and participate in Agile/DevOps workflows Clear written and verbal communication skills to present findings to technical and non-technical stakeholders Comfortable working across Git, Confluence, JIRA, & collaborative agile environments Nice To Have Experience building or contributing to the AIOps platform (e.g., Moogsoft, BigPanda, Datadog, Aisera, Dynatrace, BMC etc.) Experience working in streaming media, OTT platforms, or large-scale consumer services Exposure to Infrastructure as Code (Terraform, Pulumi) and modern cloud-native tooling Working experience with Conviva, Touchstream, Harmonic, New Relic, Prometheus, & event- based alerting tools Hands-on experience with LLMs in operational contexts (e.g., classification of alert text, log summarization, retrieval-augmented generation) Familiarity with vector databases (e.g., FAISS, Pinecone, Weaviate) and embeddings-based search for observability data Experience using MLflow, SageMaker, or Airflow for ML workflow orchestration Knowledge of LangChain, Haystack, RAG pipelines, or prompt templating libraries Exposure to MLOps practices (e.g., model monitoring, drift detection, explainability tools like SHAP or LIME) Experience with containerized model deployment using Docker or Kubernetes Use of JAX, Hugging Face Transformers, or LLaMA/Claude/Command-R models in experimentation Experience designing APIs in Python or Go to expose models as services Cloud proficiency in AWS/GCP, especially for distributed training, storage, or batch inferencing Contributions to open-source ML or DevOps communities, or participation in AIOps research/benchmarking efforts. Certifications in cloud architecture, ML engineering, or data science specializations, confluence pages, white papers, presentations, test results, technical manuals, formal recommendations and reports. Contributes to the company by creating patents, Application Programming Interfaces (APIs). Comcast is proud to be an equal opportunity workplace. We will consider all qualified applicants for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability, veteran status, genetic information, or any other basis protected by applicable law. Base pay is one part of the Total Rewards that Comcast provides to compensate and recognize employees for their work. Most sales positions are eligible for a Commission under the terms of an applicable plan, while most non-sales positions are eligible for a Bonus. Additionally, Comcast provides best-in-class Benefits to eligible employees. We believe that benefits should connect you to the support you need when it matters most, and should help you care for those who matter most. That’s why we provide an array of options, expert guidance and always-on tools, that are personalized to meet the needs of your reality – to help support you physically, financially and emotionally through the big milestones and in your everyday life. Please visit the compensation and benefits summary on our careers site for more details. Education Bachelor's Degree While possessing the stated degree is preferred, Comcast also may consider applicants who hold some combination of coursework and experience, or who have extensive related professional experience. Relevant Work Experience 5-7 Years

Job Summary As part of the data leadership team, the Capability Lead – Databricks will be responsible for building, scaling, and delivering Databricks-based data and AI capabilities across the organization. This leadership role involves technical vision, solution architecture, team building, partnership development, and delivery excellence using Databricks Unified Analytics Platform across industries. The individual will collaborate with clients, alliance partners (Databricks, Azure, AWS), internal stakeholders, and sales teams to drive adoption of lakehouse architectures, data engineering best practices, and AI/ML modernization. Areas of Responsibility 1. Offering and Capability Development: Develop and enhance Snowflake-based data platform offerings and accelerators Define best practices, architectural standards, and reusable frameworks for Snowflake Collaborate with alliance teams to strengthen partnership with Snowflake 2. Technical Leadership: Provide architectural guidance for Snowflake solution design and implementation Lead solutioning efforts for proposals, RFIs, and RFPs involving Snowflake Conduct technical reviews and ensure adherence to design standards. Act as a technical escalation point for complex project challenges 3. Delivery Oversight: Support delivery teams with technical expertise across Snowflake projects Drive quality assurance, performance optimization, and project risk mitigation. Review project artifacts and ensure alignment with Snowflake best practices Foster a culture of continuous improvement and delivery excellence 4. Talent Development: Build and grow a high-performing Snowflake capability team. Define skill development pathways and certification goals for team members. Mentor architects, developers, and consultants on Snowflake technologies Drive community of practice initiatives to share knowledge and innovations 5. Business Development Support: Engage with sales and pre-sales teams to position Snowflake capabilities Contribute to account growth by identifying new Snowflake opportunities Participate in client presentations, workshops, and technical discussions 6. Thought Leadership and Innovation Build thought leadership through whitepapers, blogs, and webinars Stay updated with Snowflake product enhancements and industry trends This role is highly collaborative and will work extremely closely with cross functional teams to fulfill the above responsibilities. Job Requirements: 12–15 years of experience in data engineering, analytics, and AI/ML 3–5 years of strong hands-on experience with Databricks (on Azure, AWS, or GCP) Expertise in Spark (PySpark/Scala), Delta Lake, Unity Catalog, MLflow, and Databricks notebooks Experience designing and implementing Lakehouse architectures at scale Familiarity with data governance, security, and compliance frameworks (GDPR, HIPAA, etc.) Experience with real-time and batch data pipelines (Structured Streaming, Auto Loader, Kafka, etc.) Strong understanding of MLOps and AI/ML lifecycle management Certifications in Databricks (e.g., Databricks Certified Data Engineer Professional, ML Engineer Associate) are preferred Experience with hyperscaler ecosystems (Azure Data Lake, AWS S3, GCP GCS, ADF, Glue, etc.) Experience managing large, distributed teams and working with CXO-level stakeholders Strong problem-solving, analytical, and decision-making skills Excellent verbal, written, and client-facing communication

About AiSensy AiSensy is a WhatsApp based Marketing & Engagement platform helping businesses like Adani, Delhi Transport Corporation, Yakult, Godrej, Aditya Birla Hindalco, Wipro, Asian Paints, India Today Group, Skullcandy, Vivo, Physicswallah, and Cosco grow their revenues via WhatsApp. Enabling 100,000+ Businesses with WhatsApp Engagement & Marketing 400 Crores+ WhatsApp Messages exchanged between Businesses and Users via AiSensy per year Working with top brands like Delhi Transport Corporation, Vivo, Physicswallah & more High Impact as Businesses drive 25-80% Revenues using AiSensy Platform Mission-Driven and Growth Stage Startup backed by Marsshot.vc, Bluelotus.vc & 50+ Angel Investors Role Overview We are looking for a Senior Machine Learning Engineer to lead the development and deployment of cutting-edge AI/ML systems with a strong focus on LLMs, Retrieval-Augmented Generation (RAG), AI agents , and intelligent automation. You will work closely with cross-functional teams to translate business needs into AI solutions, bringing your expertise in building scalable ML infrastructure, deploying models in production, and staying at the forefront of AI innovation. Key Responsibilities AI & ML System Development Design, develop, and optimize end-to-end ML models using LLMs, transformer architectures, and custom RAG frameworks. Fine-tune and evaluate generative and NLP models for business-specific applications such as conversational flows, auto-replies, and intelligent routing. Lead prompt engineering and build autonomous AI agents capable of executing multi-step reasoning. Infrastructure, Deployment & MLOps Architect and automate scalable training, validation, and deployment pipelines using tools like MLflow, SageMaker, or Vertex AI. Integrate ML models with APIs, databases (vector/graph), and production services ensuring performance, reliability, and traceability. Monitor model performance in real-time, and implement A/B testing, drift detection, and re-training pipelines. Data & Feature Engineering Work with structured, unstructured, and semi-structured data (text, embeddings, chat history). Build and manage vector databases (e.g., Pinecone, Weaviate) and graph-based retrieval systems. Ensure high-quality data ingestion, feature pipelines, and scalable pre-processing workflows. Team Collaboration & Technical Leadership Collaborate with product managers, software engineers, and stakeholders to align AI roadmaps with product goals. Mentor junior engineers and establish best practices in experimentation, reproducibility, and deployment. Stay updated on the latest in AI/ML (LLMs, diffusion models, multi-modal learning), and drive innovation in applied use cases. Required Qualifications Bachelor’s/Master’s degree in Computer Science, Engineering, AI/ML, or a related field from a Tier 1 institution (IIT, NIT, IIIT or equivalent). 2+ years of experience building and deploying machine learning models in production. Expertise in Python and known the frameworks like TensorFlow, PyTorch, Hugging Face, Scikit-learn . Hands-on experience with transformer models , LLMs , LangChain , LangGraph, OpenAI API , or similar. Deep knowledge of machine learning algorithms , model evaluation, hyperparameter tuning, and optimization. Experience working with cloud platforms (AWS, GCP, or Azure) and ML Ops tools (MLflow, Airflow, Kubernetes). Strong understanding of SQL , data engineering concepts, and working with large-scale datasets. Preferred Qualifications Experience with prompt tuning, agentic AI systems , or multi-modal learning . Familiarity with vector search systems (e.g., Pinecone, FAISS, Milvus) and knowledge graphs . Contributions to open-source AI/ML projects or publications in AI journals/conferences. Experience in building conversational AI or smart assistants using WhatsApp or similar messaging APIs. Why Join AiSensy? Build AI that directly powers growth for 100,000+ businesses. Work on cutting-edge technologies like LLMs, RAG, and AI agents in real production environments. High ownership, fast iterations, and impact-focused work. Ready to build intelligent systems that redefine communication? Apply now and join the AI revolution at AiSensy .

Job Description Alimentation Couche-Tard Inc., (ACT) is a global Fortune 200 company. A leader in the convenience store and fuel space with over 16,700 stores in 31 countries, serving more than 9 million customers each day. The India Data & Analytics Global Capability Centre is an integral part of ACT’s Global Data & Analytics Team and the Senior Data Scientist will be a key player on this team that will help grow analytics globally at ACT. The hired candidate will partner with multiple departments, including Global Marketing, Merchandising, Global Technology, and Business Units. About The Role The incumbent will be responsible for delivering advanced analytics projects that drive business results including interpreting business, selecting the appropriate methodology, data cleaning, exploratory data analysis, model building, and creation of polished deliverables. Responsibilities Analytics & Strategy Analyse large-scale structured and unstructured data; develop deep-dive analyses and machine learning models in retail, marketing, merchandising, and other areas of the business Utilize data mining, statistical and machine learning techniques to derive business value from store, product, operations, financial, and customer transactional data Apply multiple algorithms or architectures and recommend the best model with in-depth description to evangelize data-driven business decisions Utilize cloud setup to extract processed data for statistical modelling and big data analysis, and visualization tools to represent large sets of time series/cross-sectional data Operational Excellence Follow industry standards in coding solutions and follow programming life cycle to ensure standard practices across the project Structure hypothesis, build thoughtful analyses, develop underlying data models and bring clarity to previously undefined problems Partner with Data Engineering to build, design and maintain core data infrastructure, pipelines and data workflows to automate dashboards and analyses Stakeholder Engagement Working collaboratively across multiple sets of stakeholders – Business functions, Data Engineers, Data Visualization experts to deliver on project deliverables Articulate complex data science models to business teams and present the insights in easily understandable and innovative formats Job Requirements Education Bachelor’s degree required, preferably with a quantitative focus (Statistics, Business Analytics, Data Science, Math, Economics, etc.) Master’s degree preferred (MBA/MS Computer Science/M.Tech Computer Science, etc.) Relevant Experience 5–7 years of relevant working experience in a data science/advanced analytics role Behavioural Skills Delivery Excellence Business disposition Social intelligence Innovation and agility Knowledge Functional Analytics (Supply chain analytics, Marketing Analytics, Customer Analytics) Statistical modelling using Analytical tools (R, Python, KNIME, etc.) and use big data technologies Knowledge of statistics and experimental design (A/B testing, hypothesis testing, causal inference) Practical experience building scalable ML models, feature engineering, model evaluation metrics, and statistical inference. Practical experience deploying models using MLOps tools and practices (e.g., MLflow, DVC, Docker, etc.) Strong coding proficiency in Python (Pandas, Scikit-learn, PyTorch/TensorFlow, etc.) Big data technologies & framework (AWS, Azure, GCP, Hadoop, Spark, etc.) Enterprise reporting systems, relational (MySQL, Microsoft SQL Server etc.), non-relational (MongoDB, DynamoDB) database management systems and Data Engineering tools Business intelligence & reporting (Power BI, Tableau, Alteryx, etc.) Microsoft Office applications (MS Excel, etc.)

🔍 We’re Hiring: Senior AI/ML Developer (3+ Years Experience) 📍 Location: On-site 🕒 Full-Time At Metaqualt Software Pvt. Ltd. , we don’t just follow technology—we shape it. As we continue to scale our AI-driven solutions across industries, we’re looking for a Senior AI/ML Developer to join our growing team of innovators and problem-solvers. 🔧 Your Role: As a Senior AI/ML Developer, you’ll take ownership of building robust, scalable machine learning models and deploying them in real-world applications. You’ll work closely with cross-functional teams to design intelligent systems that power next-gen digital experiences. ✅ What You’ll Bring: 3+ years of hands-on experience in Machine Learning, Deep Learning, or AI product development. Strong proficiency in Python and experience with TensorFlow, PyTorch, or similar frameworks. Practical knowledge of end-to-end ML lifecycle—data preprocessing, model training, evaluation, and deployment. Experience in deploying ML models using Docker, Flask/FastAPI , and cloud platforms (AWS/GCP/Azure). A solid foundation in mathematics, statistics, and data structures. 💡 Bonus Points For: Exposure to LLMs, Generative AI , or MLOps tools (e.g., MLflow, Kubeflow). Experience with blockchain + AI integrations or interest in emerging tech convergence. Mentorship experience or technical leadership on projects. 🌟 Why Join Metaqualt? Opportunity to work on real-world AI applications across sectors. Collaborative, innovation-first work culture. Competitive compensation and flexible work model. Projects that make an impact—not just experiments. 📨 Ready to take the lead in AI innovation? Send your CV to hr@metaqualt.com Subject: AI/ML Developer – [Your Name] Let’s build intelligent systems that matter—together.

We seek an experienced Principal Data Scientist to lead our data science team and drive innovation in machine learning, advanced analytics, and Generative AI. This role blends strategic leadership with deep technical expertise across ML engineering, LLMs, deep learning, and multi-agent systems. You will be at the forefront of deploying AI-driven solutions, including agentic frameworks and LLM orchestration, to tackle complex, real-world problems at scale. Primary Stack: Languages: Python, SQL Cloud Platforms: AWS or GCP preferred ML & Deep Learning: PyTorch, TensorFlow, Scikit-learn GenAI & LLM Toolkits: Hugging Face, LangChain, OpenAI APIs, Cohere, Anthropic Agentic & Orchestration Frameworks: LangGraph, CrewAI, Agno, Autogen, AutoGPT Vector Stores & Retrieval: FAISS, Pinecone, Weaviate MLOps & Deployment: MLflow, SageMaker, Vertex AI, Kubeflow, Docker, Kubernetes, Fast API Key Responsibilities: Lead and mentor a team of 10+ data scientists and ML engineers, promoting a culture of innovation, ownership, and cross-functional collaboration. Drive the development, deployment, and scaling of advanced machine learning, deep learning, and GenAI applications across the business. Build and implement agentic architectures and multi-agent systems using tools like LangGraph, CrewAI, and Agno to solve dynamic workflows and enhance LLM reasoning capabilities. Architect intelligent agents capable of autonomous planning, decision-making, tool use, and collaboration. Leverage LLMs and transformer-based models to power solutions in NLP, conversational AI, information retrieval, and decision support. Develop and scale ML pipelines on cloud platforms, ensuring performance, reliability, and reproducibility. Establish and maintain MLOps processes (CI/CD for ML, monitoring, governance) and ensure best practices in responsible AI. Collaborate with product, engineering, and business teams to align AI initiatives with strategic goals. Stay ahead of the curve on AI/ML trends, particularly in the multi-agent and agentic systems landscape, and advocate for their responsible adoption. Present results, insights, and roadmaps to senior leadership and non-technical stakeholders in a clear, concise manner. Qualifications: 9+ years of experience in data science, business analytics, or ML engineering, with 3+ years in a leadership or principal role. Demonstrated experience in architecting and deploying LLM-based solutions in production environments. Deep understanding of deep learning, transformers, and modern NLP. Proven hands-on experience building multi-agent systems using LangGraph, CrewAI, Agno, or related tools. Strong grasp of agent design principles, including memory management, planning, tool selection, and self-reflection loops. Expertise in cloud-based ML platforms (e.g., AWS SageMaker, GCP Vertex AI) and MLOps best practices. Familiarity with retrieval-augmented generation (RAG) and vector databases (e.g., FAISS, Pinecone). Excellent communication, stakeholder engagement, and cross-functional leadership skills.

BU: Working Professional Job Title: Asst Manager- DS/ML Location: WFH Experience Required: 3-8 years Work schedule: Live Session- Monday to Friday2hrs/per day in the evening, 7:30 pm-9:30 pm Live Session- Saturday & Sunday- 10hrs/per day from 10:00 am- 10:00 pm Key Responsibilities:  Live Instruction: Teach core DS/ML topics (supervised & unsupervised learning, deep learning, model evaluation, MLOps) through interactive sessions.  Curriculum Collaboration: Work with content teams to design labs, code walkthroughs, and real-world case studies using Python, scikit-learn, TensorFlow/PyTorch, and cloud-based DS/ML services.  Learner Support: Field technical questions, debug code, review notebooks, and provide actionable feedback on assignments and projects.  Project Mentorship: Guide capstone work—e.g., image/video models, NLP pipelines, recommendation systems, and deployment pipelines.  Continuous Improvement: Analyze learner performance data to refine modules, introduce emerging topics (e.g., transformers, generative models), and enhance assessments. Requirements:  3+ years of industry or academic experience in DS/ML or AI.  Minimum Master’s degree in DS or ML &AI or CS specialization in AI & DS/ML  Proficiency in Python and ML frameworks (scikit-learn, TensorFlow or PyTorch).  Familiarity with MLOps tools (Docker, Kubernetes, MLflow) and cloud ML services (AWS SageMaker, GCP AI Platform, or Azure ML).  Excellent presentation and mentoring skills in live and small-group settings.  Prior teaching or edtech experience is a strong plus.

2 Years of experience mandatory Machine Learning (ML): Supervised & unsupervised learning Regression, classification, clustering Model evaluation and tuning Deep Learning: Neural networks (CNNs, RNNs, LSTMs, Transformers) Frameworks: TensorFlow, PyTorch, Keras Data Science & Analytics: Data cleaning and pre-processing Feature engineering EDA (Exploratory Data Analysis) Programming: Proficient in Python (NumPy, pandas, scikit-learn, matplotlib, etc.) Optional: R, Julia, or C++ NLP & LLMs: Text preprocessing, embeddings (word2vec, BERT, etc.) Fine-tuning and using LLMs (e.g., GPT, BERT, T5) Computer Vision: Image classification, object detection OpenCV, YOLO, or similar libraries Math & Stats: Linear algebra, probability, calculus Statistical modeling Infrastructure & DevOps Cloud platforms: AWS, GCP, Azure MLOps: ML pipelines, model versioning (e.g., MLflow, DVC) Docker, Kubernetes for deployment Git and version control Understanding business problems and translating them into AI solutions Job Type: Full-time Pay: ₹50,499.45 - ₹75,027.94 per month Schedule: Day shift Experience: AL/ML: 2 years (Required) Work Location: In person

Job Title - Project Manager / Scrum Master – AI Platform, Chip Design & OS Innovation Location: On-site, Hyderabad (No work-from-home) Employment Type: Full-time Experience: 5+ years in Agile project leadership About the Role We’re on a mission to build India’s most ambitious deep-tech product company — a platform that blends LLM innovation, chip design, custom operating systems, and next-gen AI applications. If that sounds like a tall order — it is. And we’re doing it anyway. This isn’t just a job. It’s a front-row seat to the next wave of AI and hardware convergence , where product innovation meets systems-level thinking. We're building something that could redefine how enterprises and developers interact with intelligence — and we’re looking for a high-impact Project Manager / Scrum Master who’s ready to lead from the front. You’ll work with cross-functional squads: Python and Flutter engineers, chip architects, OS designers, and LLM researchers — to drive execution that is nothing short of world-class. The learning curve here isn’t steep — it’s vertical. Think hockey stick . Think OpenAI + Apple + NVIDIA energy. That’s the mindset we’re hiring for. What You’ll Drive Orchestrate end-to-end sprints across LLM dev, OS architecture, and AI product delivery Align timelines between model training, GPU resource allocation, chip design milestones, and app releases Facilitate Agile rituals with precision and energy — keeping a diverse team firing on all cylinders Serve as the central node between product vision, engineering velocity, and research experimentation Maintain deep visibility using tools like JIRA, Notion, or ClickUp — and lead from the front on delivery Partner with technical and product leadership to push the boundaries of what's possible Inspire a team culture of speed, accountability, and high-bandwidth learning What You Bring 5+ years of experience leading Agile/Scrum teams in tech-first environments Deep understanding of software engineering workflows (Python, Flutter) and ML pipelines Bonus: familiarity with hardware cycles, embedded systems, or OS-level architecture Strong coordination across cross-disciplinary teams — from AI researchers to hardware designers Exposure to LLM tools like Hugging Face, MLflow, or model tuning platforms is a plus Excellent communication and roadmap ownership skills Scrum Master certifications (CSM, PSM) preferred Background in CS, ECE, or equivalent technical domain Job Types: Full-time, Permanent Pay: ₹80,000.00 - ₹90,000.00 per month Work Location: In person

We are seeking a highly skilled and hands-on AI Architect to lead the design and deployment of next-generation AI systems for our cutting-edge platform. You will be responsible for architecting scalable GenAI and machine learning solutions, establishing MLOps best practices, and ensuring robust security and cost-efficient operations across our AI-powered modules Primary Skills: • System architecture for GenAI: design scalable pipelines using LLMs, RAG, multi‐agent orchestration (LangGraph, CrewAI, AutoGen). • Machine‐learning engineering: PyTorch or TensorFlow, Hugging Face Transformers. • Retrieval & vector search: FAISS, Weaviate, Pinecone, pgvector; embedding selection and index tuning. • Cloud infra: AWS production experience (GPU instances, Bedrock / Vertex AI, EKS, IAM, KMS). • MLOps & DevOps: MLflow / Kubeflow, Docker + Kubernetes, CI/CD, Terraform • Security & compliance: data encryption, RBAC, PII redaction in LLM prompts. • Cost & performance optimisation: token‐usage budgeting, caching, model routing. • Stakeholder communication: ability to defend architectural decisions to CTO, product, and investors.

Job Title: AI Developer Company: Eoxys IT Solution Location: Jaipur, Rajasthan Experience: 1–2 Years Employment Type: Full-Time Education Qualification: BCA / MCA / B.Tech in Computer Science, IT, or related field Key Skills Required: Strong programming skills in Python Hands-on experience with TensorFlow , PyTorch , Keras Experience building and deploying end-to-end ML pipelines Solid understanding of model evaluation , cross-validation , and hyperparameter tuning Familiarity with cloud platforms such as AWS, Azure, or GCP for AI/ML workloads Knowledge of MLOps tools like MLflow, DVC, or Apache Airflow Exposure to domains like Natural Language Processing (NLP) , Computer Vision , or Reinforcement Learning Roles & Responsibilities: Develop, train, and deploy machine learning models for real-world applications Implement scalable ML solutions using cloud platforms Collaborate with cross-functional teams to integrate AI capabilities into products Monitor model performance and conduct regular improvements Maintain version control and reproducibility using MLOps practices Additional Requirements: Strong analytical and problem-solving skills Passion for learning and implementing cutting-edge AI/ML technologies Good communication and teamwork skills Salary: Based on experience and skillset Apply Now to be a part of our innovative AI journey! Job Type: Full-time Pay: ₹15,000.00 - ₹40,000.00 per month Work Location: In person

About Position: We are conducting an in-person hiring drive for the position of Mlops / Data Science in Pune & Bengaluru on 2nd August 2025.Interview Location is mentioned below: Pune – Persistent Systems, Veda Complex, Rigveda-Yajurveda-Samaveda-Atharvaveda Plot No. 39, Phase I, Rajiv Gandhi Information Technology Park, Hinjawadi, Pune, 411057 Bangalore - Persistent Systems, The Cube at Karle Town Center Rd, DadaMastan Layout, Manayata Tech Park, Nagavara, Bengaluru, Karnataka 560024 We are looking for an experienced and talented Data Science to join our growing data competency team. The ideal candidate will have a strong background in working with GEN AI , ML ,LangChain, LangGraph, Mlops Architecture Strategy, Prompt engineering. You will work closely with our data analysts, engineers, and business teams to ensure optimal performance, scalability, and availability of our data pipelines and analytics. Role: Mlops, Data Science Job Location: All PSL Location Experience: 5+ Years Job Type: Full Time Employment What You'll Do: Design, build, and manage scalable ML model deployment pipelines (CI/CD for ML). Automate model training, validation, monitoring, and retraining workflows. Implement model governance, versioning, and reproducibility best practices. Collaborate with data scientists, engineers, and product teams to operationalize ML solutions. Ensure robust monitoring and performance tuning of deployed models Expertise You'll Bring: Strong experience with MLOps tools & frameworks (MLflow, Kubeflow, SageMaker, Vertex AI, etc.). Proficient in containerization (Docker, Kubernetes). Good knowledge of cloud platforms (AWS, Azure, or GCP). Expertise in Python and familiarity with ML libraries (TensorFlow, PyTorch, scikit-learn). Solid understanding of CI/CD, infrastructure as code, and automation tools. Benefits: Competitive salary and benefits package Culture focused on talent development with quarterly promotion cycles and company-sponsored higher education and certifications Opportunity to work with cutting-edge technologies Employee engagement initiatives such as project parties, flexible work hours, and Long Service awards Annual health check-ups Insurance coverage: group term life, personal accident, and Mediclaim hospitalization for self, spouse, two children, and parents Inclusive Environment: Persistent Ltd. is dedicated to fostering diversity and inclusion in the workplace. We invite applications from all qualified individuals, including those with disabilities, and regardless of gender or gender preference. We welcome diverse candidates from all backgrounds. We offer hybrid work options and flexible working hours to accommodate various needs and preferences. Our office is equipped with accessible facilities, including adjustable workstations, ergonomic chairs, and assistive technologies to support employees with physical disabilities. If you are a person with disabilities and have specific requirements, please inform us during the application process or at any time during your employment. We are committed to creating an inclusive environment where all employees can thrive. Our company fosters a values-driven and people-centric work environment that enables our employees to: Accelerate growth, both professionally and personally Impact the world in powerful, positive ways, using the latest technologies Enjoy collaborative innovation, with diversity and work-life wellbeing at the core Unlock global opportunities to work and learn with the industry’s best Let’s unleash your full potential at Persistent “Persistent is an Equal Opportunity Employer and prohibits discrimination and harassment of any kind.”

SLSQ326R415 Databricks is at the forefront of the Unified Data Analytics field, where innovation is key to providing our clients with a competitive edge in today's fast-paced business landscape. We are looking for a Business Development Representative to help drive revenue growth within the India Market. If you're a results-oriented sales professional with a track record in similar roles, aiming to contribute to the expansion of a transformative enterprise software company and propel your career, this role is for you. Reporting to the Manager of the India Sales Development team, you'll play a pivotal role in this journey. The Impact You Will Have Cultivate expertise in value-based selling, big data, and AI. Evaluate and prioritize the inbound leads from Marketing initiatives. Craft outbound strategies encompassing personalized emails, cold calls, and social selling to qualify opportunities. Devise compelling outreach campaigns targeting diverse buyer levels, including senior executives, to unlock opportunities in critical target accounts. Identify and uncover client requirements, progressing discussions into sales prospects by demonstrating how Databricks can address their data-related challenges. What We Look For Preferably a minimum of 1-2 years of prior experience in inbound and outbound sales and inquiries. Proficiency in comprehending technical concepts, coupled with genuine enthusiasm for technology. Determination and courage to excel and contribute to the growth of the next top-tier enterprise software company. Demonstrated a history of consistent, quantifiable achievements in previous roles. Curiosity and eagerness to continually learn and stay abreast of developments in the big data/AI sector. A strong sense of ownership and accountability. About Databricks Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook. Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region, please visit https://www.mybenefitsnow.com/databricks. Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.

Hi Connections, Urgent - Hiring for below role About the Role: We are seeking a seasoned and highly skilled MLOps Engineer to join our growing team. The ideal candidate will have extensive hands-on experience with deploying, monitoring, and retraining machine learning models in production environments. You will be responsible for building and maintaining robust and scalable MLOps pipelines using tools like MLflow, Apache Airflow, Kubernetes, and Databricks or Azure ML. A strong understanding of infrastructure-as-code using Terraform is essential. You will play a key role in operationalizing AI/ML systems and ensuring high performance, availability, and automation across the ML lifecycle. --- Key Responsibilities: · Design and implement scalable MLOps pipelines for model training, validation, deployment, and monitoring. · Operationalize machine learning models using MLflow, Airflow, and containerized deployments via Kubernetes. · Automate and manage ML workflows across cloud platforms such as Azure ML or Databricks. · Develop infrastructure using Terraform for consistent and repeatable deployments. · Trace API calls to LLMs, Azure OCR and Paradigm · Implement performance monitoring, alerting, and logging for deployed models using custom and third-party tools. · Automate model retraining and continuous deployment pipelines based on data drift and model performance metrics. · Ensure traceability, reproducibility, and auditability of ML experiments and deployments. · Collaborate with Data Scientists, ML Engineers, and DevOps teams to streamline ML workflows. · Apply CI/CD practices and version control to the entire ML lifecycle. · Ensure secure, reliable, and compliant deployment of models in production environments. --- Required Qualifications: · 5+ years of experience in MLOps, DevOps, or ML engineering roles, with a focus on production ML systems. · Proven experience deploying machine learning models using MLflow and workflow orchestration with Apache Airflow. · Hands-on experience with Kubernetes for container orchestration in ML deployments. · Proficiency with Databricks and/or Azure ML, including model training and deployment capabilities. · Solid understanding and practical experience with Terraform for infrastructure-as-code. · Experience automating model monitoring and retraining processes based on data and model drift. · Knowledge of CI/CD tools and principles applied to ML systems. · Familiarity with monitoring tools and observability stacks (e.g., Prometheus, Grafana, Azure Monitor). · Strong scripting skills in Python · Deep understanding of ML lifecycle challenges including model versioning, rollback, and scaling. · Excellent communication skills and ability to collaborate across technical and non-technical teams. --- Nice to Have: · Experience with Azure DevOps or GitHub Actions for ML CI/CD. · Exposure to model performance optimization and A/B testing in production environments. · Familiarity with feature stores and online inference frameworks. · Knowledge of data governance and ML compliance frameworks. · Experience with ML libraries like scikit-learn, PyTorch, or TensorFlow. --- Education: · Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field.

Location: Remote (India-based preferred) Type: Full-time | Founding Team | High Equity Company: Flickd (www.flickd.in) About the Role We’re building India’s most advanced virtual try-on engine — think Doji meets TryOnDiffusion, but optimized for real-world speed, fashion, and body diversity. As our ML Engineer (Computer Vision + Try-On) , you’ll own the end-to-end pipeline : from preprocessing user/product images to generating hyper-realistic try-on results with preserved pose, skin, texture, and identity. You’ll have full autonomy to build, experiment, and ship — working directly with React, Spring Boot, DevOps, and design folks already in place. This is not a junior researcher role. This is one person building the brain of the system - and setting the foundation for India's biggest visual shopping innovation. What You’ll Build Stage 1: User Image Preprocessing Human parsing (face, body, hair), pose detection, face/limb alignment Auto orientation, canvas resizing, brightness/contrast normalization Stage 2: Product Image Processing Background removal, garment segmentation (SAM/U^2-Net/YOLOv8) Handle occlusions, transparent clothes, long sleeves, etc. Stage 3: Try-On Engine Implement and iterate on CP-VTON / TryOnDiffusion / FlowNet Fine-tune on custom data for realism, garment drape, identity retention Inference Optimisation TorchScript / ONNX, batching, inference latency minimization Collaborate with DevOps for Lambda/EC2 + GPU deployment Postprocessing Alpha blending, edge smoothing, fake shadows, cloth-body warps You’re a Fit If You: Have 2–5 years in ML/CV with real shipped work (not just notebooks) Have worked on: human parsing, pose estimation, cloth warping, GANs Are hands-on with PyTorch , OpenCV, Segmentation Models, Flow or ViT Can replicate models from arXiv fast, and care about output quality Want to own a system seen by millions , not just improve metrics Stack You’ll Use PyTorch, ONNX, TorchScript, Hugging Face DensePose, OpenPose, Segment Anything, Diffusion Models Docker, Redis, AWS Lambda, S3 (infra is already set up) MLflow or DVC (can be implemented from scratch) For exceptional talent, we’re flexible on cash vs equity split. Why This Is a Rare Opportunity Build the core AI product that powers a breakout consumer app Work in a zero BS, full-speed team (React, SpringBoot, DevOps, Design all in place) Be the founding ML brain and shape all future hires Ship in weeks, not quarters — and see your output in front of users instantly Apply now, or DM Dheekshith (Founder) on LinkedIn with your GitHub or project links. Let’s build something India’s never seen before.