3 Tensorflowpytorch Jobs

Lead a team of 4-8 data scientists to develop machine learning capabilities within a Databricks-Azure platform. Provide guidance on delivering complex machine learning systems that are in line with product and platform objectives. Strive to maintain a balance between scientific rigor and practical engineering principles. Define the model lifecycle, tooling, and architectural direction for the projects. The ideal candidate should possess advanced skills in machine learning including supervised and unsupervised modeling, time-series analysis, interpretability, MLflow, Spark, and TensorFlow/PyTorch. Additionally, expertise in engineering aspects such as feature pipelines, model serving, CI/CD practices, and production deployment is required. Strong leadership abilities are essential for mentoring team members, ensuring architectural alignment across subsystems, and devising an effective experimentation strategy. Effective communication skills are crucial for translating machine learning outcomes into tangible business impact. As part of the benefits, you will have the opportunity to engage in Proximity Talks, where you can interact with other professionals in the industry, including designers, engineers, and product experts, to enhance your knowledge and skills. Working alongside a world-class team, you will be constantly challenged and encouraged to learn something new each day. Proximity is a reputable technology, design, and consulting partner for leading Sports, Media, and Entertainment companies globally. Headquartered in San Francisco, with offices in Palo Alto, Dubai, Mumbai, and Bangalore, Proximity has been instrumental in creating high-impact, scalable products utilized by 370 million daily users, with a cumulative net worth of $45.7 billion among client companies. Joining Proximity means becoming part of a global team of coders, designers, product managers, and experts dedicated to solving complex problems and developing cutting-edge technology at scale. The rapidly growing team of Proxonauts offers the opportunity to make a significant impact on the company's success. You will collaborate with experienced leaders who have successfully led multiple tech, product, and design teams. To learn more about us, you can watch our CEO, Hardik Jagda, share insights about Proximity, explore our values and meet team members, visit our website, blog, and design studio at Studio Proximity, and get an insider's view of our operations on Instagram by following @ProxWrks and @H.Jagda.,

You are a highly skilled and motivated Lead Data Scientist / Machine Learning Engineer sought to join a team pivotal in the development of a cutting-edge reporting platform. This platform is designed to measure and optimize online marketing campaigns effectively. Your role will involve focusing on data engineering, ML model lifecycle, and cloud-native technologies. You will be responsible for designing, building, and maintaining scalable ELT pipelines, ensuring high data quality, integrity, and governance. Additionally, you will develop and validate predictive and prescriptive ML models to enhance marketing campaign measurement and optimization. Experimenting with different algorithms and leveraging various models will be crucial in driving insights and recommendations. Furthermore, you will deploy and monitor ML models in production and implement CI/CD pipelines for seamless updates and retraining. You will work closely with data analysts, marketing teams, and software engineers to align ML and data solutions with business objectives. Translating complex model insights into actionable business recommendations and presenting findings to stakeholders will also be part of your responsibilities. Qualifications & Skills: Educational Qualifications: - Bachelors or Masters degree in Computer Science, Data Science, Machine Learning, Artificial Intelligence, Statistics, or related field. - Certifications in Google Cloud (Professional Data Engineer, ML Engineer) is a plus. Must-Have Skills: - Experience: 5-10 years with the mentioned skillset & relevant hands-on experience. - Data Engineering: Experience with ETL/ELT pipelines, data ingestion, transformation, and orchestration (Airflow, Dataflow, Composer). - ML Model Development: Strong grasp of statistical modeling, supervised/unsupervised learning, time-series forecasting, and NLP. - Programming: Proficiency in Python (Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch) and SQL for large-scale data processing. - Cloud & Infrastructure: Expertise in GCP (BigQuery, Vertex AI, Dataflow, Pub/Sub, Cloud Storage) or equivalent cloud platforms. - MLOps & Deployment: Hands-on experience with CI/CD pipelines, model monitoring, and version control (MLflow, Kubeflow, Vertex AI, or similar tools). - Data Warehousing & Real-time Processing: Strong knowledge of modern data platforms for batch and streaming data processing. Nice-to-Have Skills: - Experience with Graph ML, reinforcement learning, or causal inference modeling. - Working knowledge of BI tools (Looker, Tableau, Power BI) for integrating ML insights into dashboards. - Familiarity with marketing analytics, attribution modeling, and A/B testing methodologies. - Experience with distributed computing frameworks (Spark, Dask, Ray). Location: - Bengaluru Brand: - Merkle Time Type: - Full time Contract Type: - Permanent,

AI Opportunities with Soul AIs Expert Community! Are you an MLOps Engineer ready to take your expertise to the next levelSoul AI (by Deccan AI) is building an elite network of AI professionals, connecting top-tier talent with cutting-edge projects, Why Join Above market-standard compensation Contract-based or freelance opportunities (212 months) Work with industry leaders solving real AI challenges Flexible work locations Remote | Onsite | Hyderabad/Bangalore Your Role: Architect and optimize ML infrastructure with Kubeflow, MLflow, SageMaker Pipelines Build CI/CD pipelines (GitHub Actions, Jenkins, GitLab CI/CD) Automate ML workflows (feature engineering, retraining, deployment) Scale ML models with Docker, Kubernetes, Airflow Ensure model observability, security, and cost optimization in cloud (AWS/GCP/Azure) Must-Have Skills: Proficiency in Python, TensorFlow, PyTorch, CI/CD pipelines Hands-on experience with cloud ML platforms (AWS SageMaker, GCP Vertex AI, Azure ML) Expertise in monitoring tools (MLflow, Prometheus, Grafana) Knowledge of distributed data processing (Spark, Kafka) (Bonus: Experience in A/B testing, canary deployments, serverless ML) Next Steps: Register on Soul AIs website Get shortlisted & complete screening rounds Join our Expert Community and get matched with top AI projects Dont just find a job Build your future in AI with Soul AI!