Data Science Intern

SENIOR DATA ENGINEER:

ROLE SUMMARY:

Own the design and delivery of petabyte-scale data platforms and pipelines across AWS and modern Lakehouse stacks. You’ll architect, code, test, optimize, and operate ingestion, transformation, storage, and serving layers. This role requires autonomy, strong engineering judgment, and partnership with project managers, infrastructure teams, testers, and customer architects to land secure, cost-efficient, and high-performing solutions.

RESPONSIBILITIES:

• Architecture and design: Create HLD/LLD/SAD, source–target mappings, data contracts, and optimal designs aligned to requirements.
• Pipeline development: Build and test robust ETL/ELT for batch, micro-batch, and streaming across RDBMS, flat files, APIs, and event sources.
• Performance and cost tuning: Profile and optimize jobs, right-size infrastructure, and model license/compute/storage costs.
• Data modeling and storage: Design schemas and SCD strategies; manage relational, NoSQL, data lakes, Delta Lakes, and Lakehouse tables.
• DevOps and release: Establish coding standards, templates, CI/CD, configuration management, and monitored release processes.
• Quality and reliability: Define DQ rules and lineage; implement SLA tracking, failure detection, RCA, and proactive defect mitigation.
• Security and governance: Enforce IAM best practices, retention, audit/compliance; implement PII detection and masking.
• Orchestration: Schedule and govern pipelines with Airflow and serverless event-driven patterns.
• Stakeholder collaboration: Clarify requirements, present design options, conduct demos, and finalize architectures with customer teams.
• Leadership: Mentor engineers, set FAST goals, drive upskilling and certifications, and support module delivery and sprint planning.

REQUIRED QUALIFICATIONS:

• Experience: 15+ years designing distributed systems at petabyte scale; 10+ years building data lakes and multi-source ingestion.
•  Cloud (AWS): IAM, VPC, EC2, EKS/ECS, S3, RDS, DMS, Lambda, CloudWatch, CloudFormation, CloudTrail.
• Programming: Python (preferred), PySpark, SQL for analytics, window functions, and performance tuning.
• ETL tools: AWS Glue, Informatica, Databricks, GCP DataProc; orchestration with Airflow.
• Lakehouse/warehousing: Snowflake, BigQuery, Delta Lake/Lakehouse; schema design, partitioning, clustering, performance optimization.
• DevOps/IaC: Terraform with 15+ years of practice; CI/CD (GitHub Actions, Jenkins) with 10+ years; config governance and release management.
• Serverless and events: Design event-driven distributed systems on AWS.
• NoSQL: 2–3 years with DocumentDB including data modeling and performance considerations.
• AI services: AWS Entity Resolution, AWS Comprehend; run custom LLMs on Amazon SageMaker; use LLMs for PII classification.

NICE-TO-HAVE QUALIFICATIONS:

• Data governance automation: 10+ years defining audit, compliance, retention standards and automating governance workflows.
• Table and file formats: Apache Parquet; Apache Iceberg as analytical table format.
• Advanced LLM workflows: RAG and agentic patterns over proprietary data; re-ranking with index/vector store results.
• Multi-cloud exposure: Azure ADF/ADLS, GCP Dataflow/DataProc; FinOps practices for cross-cloud cost control.

OUTCOMES AND MEASURES:

• Engineering excellence: Adherence to processes, standards, and SLAs; reduced defects and non-compliance; fewer recurring issues.
• Efficiency: Faster run times and lower resource consumption with documented cost models and performance baselines.
• Operational reliability: Faster detection, response, and resolution of failures; quick turnaround on production bugs; strong release success.
• Data quality and security: High DQ pass rates, robust lineage, minimal security incidents, and audit readiness.
• Team and customer impact: On-time milestones, clear communication, effective demos, improved satisfaction, and completed certifications/training.

LOCATION AND SCHEDULE:

●      Location: Outside US (OUS).

●      Schedule: Minimum 6 hours of overlap with US time zones.

Job Summary:

Core Technical Skills

Strong JavaScript OR TypeScript experience (minimum 2 years)

Angular OR good balance of JS/TS + Angular skills

Understanding of HTTP requests & web technologies

Hands-on project experience in JavaScript ecosystem

Good to have (not mandatory):

Node.js

XPath

Puppeteer

Automation scripting exposure

Coding & Development Skills

Building and maintaining UI components

Writing clean, maintainable code

• Debugging & troubleshooting in production/test environments

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Thirega@ vysystems dot com - WhatsApp - 91Five0033Five2Three

Senior Software Engineer

Location: On-site, Panaji, Goa

About Joyful

Joyful is a leading AI-powered stakeholder communication management platform for voice of stakeholder analysis and contact center solutions. Our mission is to use AI to make all interactions between a company and its stakeholders joyful by removing friction. Joyful is a part of Germinait Solutions Pvt. Ltd.

Our  Joyful modules, Engage and Listen, help businesses understand and manage stakeholder interactions across digital channels. We enable companies to provide exceptional customer experiences while maximizing the productivity and efficiency of their support teams, all through one seamless platform.

At Joyful, we're committed to fostering meaningful interactions between stakeholders and brands by providing actionable insights, personalized replies, and a joyful experience for customers, users, and employees alike.

The Opportunity

We’re seeking a Senior Software Engineer who thrives on solving complex problems, architecting scalable systems, and bringing innovative AI-powered features to life. You will work on a modern, cloud-native stack—leveraging serverless deployment, microservices, and AI/ML integrations to build resilient, high-performance solutions.

In addition to delivering high-quality code, you’ll contribute to Joyful’s Vibe Coding culture—our approach to writing code that’s clean, collaborative, and a joy to work with.

What You'll Do

• Backend & Cloud Development
• Design, develop, and maintain scalable microservices for Joyful’s Engage and Listen platforms
• Build serverless applications and functions (AWS Lambda, Azure Functions, or GCP Cloud Functions) for rapid, cost-effective deployments
• Implement robust APIs and data pipelines optimized for performance and reliability
• Ensure security, compliance, and data privacy in all backend services
• AI-Powered Solutions
• Integrate AI/ML models into production workflows to enhance automation, personalization, and analytics
• Collaborate with data scientists to operationalize AI models for real-time and batch processing
• Build features that leverage NLP, sentiment analysis, and predictive analytics for stakeholder communication insights
• Vibe Coding Culture
• Write clean, well-structured, and maintainable code that engineers enjoy working with
• Participate in pair programming, peer reviews, and collaborative debugging sessions
• Share best practices and mentor junior engineers to raise the technical bar across the team
• Help maintain a development atmosphere that’s positive, creative, and focused on continuous improvement
• DevOps & Deployment
• Work closely with DevOps teams to optimize serverless deployments, CI/CD pipelines, and automated testing
• Ensure observability, monitoring, and alerting systems are in place for all deployed services
• Contribute to cost optimization strategies for serverless architectures
• Collaboration & Problem-Solving
• Partner with product managers, architects, and designers to translate business requirements into technical solutions
• Participate in sprint planning, backlog refinement, and retrospectives
• Troubleshoot production issues and drive root cause analysis for lasting fixes

What You'll Need

• 3+ years of experience in software development, preferably in SaaS or AI-driven products
• Strong expertise in backend development using Java (Spring Boot), Node.js, or Python
• Experience with serverless architectures (AWS Lambda, Azure Functions, or GCP equivalents)
• Solid understanding of cloud services (AWS, Azure, or GCP) and microservices design patterns
• Hands-on experience integrating AI/ML models into applications
• Familiarity with NLP, speech-to-text, or sentiment analysis APIs is a plus
• Knowledge of relational and NoSQL databases (PostgreSQL, DynamoDB, MongoDB, etc.)
• Experience with CI/CD pipelines, automated testing, and monitoring tools
• Strong problem-solving skills and ability to work in fast-paced, collaborative environments
• Passion for clean, maintainable code and contributing to a healthy team culture

Why Join Joyful?

• Work on AI-powered solutions that transform how businesses connect with their stakeholders
• Be part of a team that embraces serverless-first development and modern cloud-native architectures
• Thrive in a Vibe Coding culture where great engineering meets great energy
• Collaborate with talented peers in a supportive, innovation-driven environment
• Enjoy professional growth opportunities in a fast-scaling company
• Work from our beautiful Goa office while building solutions used worldwide

At Joyful, we believe that combining AI innovation, scalable cloud design, and a joyful coding culture leads to exceptional products. If you’re passionate about building intelligent, high-performance systems while keeping the engineering vibe positive, we’d love to hear from you!

Job Title: Chief Engineer: Deep Learning Compiler Expert

You will collaborate with experts in machine learning, algorithms and software to lead our effort of deploying machine learning models onto Samsung Mobile AI platform.

In this position, you will contribute, develop and enhance our compiler infrastructure for high-performance by using open-source technology like MLIR, LLVM, TVM and IREE.

Necessary Skills / Attributes:

• 6 to 15 years of experience in the field of compiler design and graph mapping.
• 2+ years hands-on experience with MLIR and/or LLVM.
• Experience with multiple toolchains, compilers, and Instruction Set Architectures.
• Strong knowledge of resource management, scheduling, code generation, and compute graph optimization.
• Strong expertise in writing modern standards (C++17 or newer) C++ production quality code along test-driven development principles.
• Comfortable and experienced in software development life cycle - coding, debugging, optimization, testing, and continuous integration.
• Familiarity with parallelization techniques for ML acceleration.
• Experience working on and contributing to an active compiler toolchain codebase, such as LLVM, MLIR, or Glow.
• Experience in deep learning algorithms and techniques, e.g., convolutional neural networks, recurrent networks, etc.
• Experience of developing in a mainstream machine-learning framework, e.g. PyTorch, Tensorflow or Caffe.
• Experience operating in a fast-moving environment where the workloads evolve at a rapid pace.
• Understanding of the interplay of hardware and software architectures on future algorithms, programming models and applications.
• Experience developing innovative architectures to extend the state of the art in DL performance and efficiency.
• Experience with Hardware and Software Co-design.

M.S. or higher degree, in CS/CE/EE or equivalent with industry or open-source experience.

Work Profile:

• Design, implement and test compiler features and capabilities related to infrastructure and compiler passes.
• Ingest CNN graphs in Pytorch/TF/TFLite/ONNX format and map them to hardware implementations, model data-flows, create resource utilization cost-benefit analysis and estimate silicon performance.
• Develop graph compiler optimizations (operator fusion, layout optimization, etc) that are customized to each of the different ML accelerators in the system.
• Integrate open-source and vendor compiler technology into Samsung ML internal compiler infrastructure.
• Collaborate with Samsung ML acceleration platform engineers to guide the direction of inferencing and provide requirements and feature requests for hardware vendors.
• Closely follow industry and academic developments in the ML compiler domain and provide performance guidelines and standard methodologies for other ML engineers.
• Create and optimize compiler backend to leverage the full hardware potential, efficiently optimizing them using novel approaches.
• Evaluate code performance, debug, diagnose and drive resolution of compiler and cross-disciplinary system issues.
• Contribute to the development of machine-learning libraries, intermediate representations, export formats and analysis tools.
• Communicate and collaborate effectively with cross-functional hardware and software engineering teams.
• Champion engineering and operational excellence, establishing metrics and processes for regular assessment and improvement.

Keywords to source candidates

Senior Developer, Deep Learning, Prediction engine, Machine Learning, Compiler