Engineer 3 in India

A BOUT TIDE At Tide, we help SMEs save time and money in the running of their businesses by not only offering business accounts and related banking services, but also a comprehensive set of highly usable and connected administrative solutions, from invoicing to accounting. Tide is transforming the small business banking market and now supports over 2 million members globally across the UK, India, Germany and France. Using advanced technology, all solutions are designed with SMEs in mind. With quick onboarding, low fees and innovative features, we thrive on making data driven decisions to serve our mission: to help SMEs save time and money so they can get back to doing what they love. Tide facts: Tide is available for UK, Indian, German and French SMEs Over 2 million members across UK and India Over $300 million raised in funding Over 2,800 Tideans globally Recognised with Great Place to Work certification three years in a row, and among India’s Top 50 Best Workplaces in Banking, Financial Services, and Insurance in 2026 We have offices in Central London, with a member support and technology centre in Sofia, Bulgaria, technology centres in Serbia, Romania, Lithuania and Hyderabad and offices in Gurugram, New Delhi, Berlin, Paris and Luxembourg ABOUT THE TEAM: The Product Security team at Tide is responsible for embedding security across the full product surface, from secure design and threat modelling through to application-layer controls and vulnerability management. Within Product Security, the Remediation Operations function owns the day-to-day engine of Tide's vulnerability management programme: turning a high volume of findings from across our tooling estate into clear, prioritised, actionable work for engineering and IT teams. This role sits at the heart of that function. You will be the connective tissue between security tooling and the teams who fix things, making sure the right vulnerabilities reach the right people with the right context, and that the

A BOUT TIDE At Tide, we help SMEs save time and money in the running of their businesses by not only offering business accounts and related banking services, but also a comprehensive set of highly usable and connected administrative solutions, from invoicing to accounting. Tide is transforming the small business banking market and now supports over 2 million members globally across the UK, India, Germany and France. Using advanced technology, all solutions are designed with SMEs in mind. With quick onboarding, low fees and innovative features, we thrive on making data driven decisions to serve our mission: to help SMEs save time and money so they can get back to doing what they love. Tide facts: Tide is available for UK, Indian, German and French SMEs Over 2 million members across UK and India Over $300 million raised in funding Over 2,800 Tideans globally Recognised with Great Place to Work certification three years in a row, and among India’s Top 50 Best Workplaces in Banking, Financial Services, and Insurance in 2026 We have offices in Central London, with a member support and technology centre in Sofia, Bulgaria, technology centres in Serbia, Romania, Lithuania and Hyderabad and offices in Gurugram, New Delhi, Berlin, Paris and Luxembourg ABOUT THE TEAM: The Product Security team at Tide is responsible for embedding security across the full product surface, from secure design and threat modelling through to application-layer controls and vulnerability management. Within Product Security, the Remediation Operations function owns the day-to-day engine of Tide's vulnerability management programme: turning a high volume of findings from across our tooling estate into clear, prioritised, actionable work for engineering and IT teams. This role sits at the heart of that function. You will be the connective tissue between security tooling and the teams who fix things, making sure the right vulnerabilities reach the right people with the right context, and that the

About the Role Adobe is seeking a Machine Learning Engineer to join the Adobe Genuine Engineering team. This group protects Adobe's ecosystem from fraud, abuse, and misuse using intelligent systems worldwide. In this position, you will build and develop machine learning models from scratch, including custom transformer-based frameworks, to identify fraudulent actions, stop account sharing, and protect the experience of hundreds of millions of users. You will manage the entire model lifecycle: raw behavioral data and feature engineering, architecture development, large-scale GPU training, deployment, and monitoring. The team is actively building in-house behavioral foundation models that learn identity-preserving representations from long sequences of user activity. This is a role for an engineer who wants to own deep learning systems end-to-end — not consume pre-built ones. Key Responsibilities Build and train deep learning models from scratch, including custom transformer and attention-based architectures for long behavioral event sequences. Own the full training stack: event tokenization, temporal and positional embeddings, self-supervised pretraining (e.g., masked modeling, contrastive learning), and downstream fine-tuning. Train large models efficiently on GPU infrastructure using mixed-precision training, gradient accumulation/checkpointing, efficient attention, and distributed strategies (DDP, FSDP, or equivalent). Build and optimize feature pipelines on Databricks and Spark, transforming raw behavioral events into high-quality model inputs. Translate prototypes into production ML systems — scalable, reliable, and observable — and drive inference performance through architectural and serving-side optimization. Contribute to MLOps practices: experiment tracking, model versioning, CI/CD, automated retraining, and

About the Role Adobe is seeking a Machine Learning Engineer to join the Adobe Genuine Engineering team. This group protects Adobe's ecosystem from fraud, abuse, and misuse using intelligent systems worldwide. In this position, you will build and develop machine learning models from scratch, including custom transformer-based frameworks, to identify fraudulent actions, stop account sharing, and protect the experience of hundreds of millions of users. You will manage the entire model lifecycle: raw behavioral data and feature engineering, architecture development, large-scale GPU training, deployment, and monitoring. The team is actively building in-house behavioral foundation models that learn identity-preserving representations from long sequences of user activity. This is a role for an engineer who wants to own deep learning systems end-to-end — not consume pre-built ones. Key Responsibilities Build and train deep learning models from scratch, including custom transformer and attention-based architectures for long behavioral event sequences. Own the full training stack: event tokenization, temporal and positional embeddings, self-supervised pretraining (e.g., masked modeling, contrastive learning), and downstream fine-tuning. Train large models efficiently on GPU infrastructure using mixed-precision training, gradient accumulation/checkpointing, efficient attention, and distributed strategies (DDP, FSDP, or equivalent). Build and optimize feature pipelines on Databricks and Spark, transforming raw behavioral events into high-quality model inputs. Translate prototypes into production ML systems — scalable, reliable, and observable — and drive inference performance through architectural and serving-side optimization. Contribute to MLOps practices: experiment tracking, model versioning, CI/CD, automated retraining, and

Job Description: Data & Analytics Engineer (3-4 Years Experience) : 100% Remote Job Title: Data & Analytics Engineer Experience: 3-4 years Location: Remote Employment Type: Full-time Team: Data Engineering & Analytics About the Role Eltropy is a digital conversations platform for credit unions and community financial institutions in the US. The Data Engineering & Analytics team builds the AWS data pipelines and customer-facing dashboards that power analytics across the platform. We are looking for a Data & Analytics Engineer with 3-4 years of experience who can own dashboard delivery end to end along with the pipelines behind it. The ideal candidate learns fast, builds product context quickly, listens well, and collaborates effectively across product, engineering, DevOps, and customer-facing teams. Key Responsibilities Own dashboard changes end to end in QuickSight and ThoughtSpot - new metrics and filters, SPICE refresh management, internal-to-production promotion, and post-release validation. Build and maintain batch and streaming ETL pipelines on AWS using Glue (PySpark), S3, Redshift, and Airflow (MWAA) DAGs. Write and optimize Redshift SQL; debug query performance, connection contention, and data mismatches across sources. Support near-real-time ingestion (Kafka/MSK CDC → Glue Streaming → S3 → Redshift). Investigate customer-reported analytics discrepancies (Jira/support tickets), root-cause them in the data, and communicate findings clearly to support, product, and engineering. Set up and respond to pipeline monitoring - CloudWatch metrics and alarms, monitoring DAGs, refresh health - and participate in incident triage and RCA. Develop deep product knowledge: understand what each metric means to our credit union customers and translate product changes into data model and dashboard updates. Ensure data quality, validation, and consistency across systems. Required Skills & Qualifications 3-4 years of experience in data engineering and/or

Roles and Responsibilities Write maintainable/scalable/e?cient code. Work in a cross-functional team, collaborating with peers during the entire SDLC. Follow coding standards, unit-testing, code reviews etc. Follow release cycles and commitment to deadlines. Qualifications & Experience Experience level of 3 to 5 years of experience in very large scale applications. Fair understanding in problem solving skills, data structures and algorithms. Experience with distributed systems handling large amounts of data. Fair understanding in coding skills in Java/J2EE, Web technologies, RDBMS/messaging.

Roles and Responsibilities Write maintainable/scalable/code Work in a cross-functional team, collaborating with peers during the entire SDLC. Follow coding standards, unit-testing, code reviews etc. Follow release cycles and commitment to deadlines. Qualifications & Experience Experience level of 3 to 6 years of experience in very large scale applications. Fair understanding in problem solving skills, data structures and algorithms. Experience with distributed systems handling large amounts of data. Fair understanding in coding skills in Java/J2EE, Web technologies, RDBMS/messaging.

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