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1. Data Engineer

 Required skill set: AWS GLUE, AWS LAMBDA, AWS SNS/SQS, AWS ATHENA, SPARK, SNOWFLAKE, PYTHON

Mandatory Requirements  

• Experience in AWS Glue
• Experience in Apache Parquet 
• Proficient in AWS S3 and data lake 
• Knowledge of Snowflake
• Understanding of file-based ingestion best practices.
• Scripting language - Python & pyspark 

CORE RESPONSIBILITIES 

• Create and manage cloud resources in AWS 
• Data ingestion from different data sources which exposes data using different technologies, such as: RDBMS, REST HTTP API, flat files, Streams, and Time series data based on various proprietary systems. Implement data ingestion and processing with the help of Big Data technologies 
• Data processing/transformation using various technologies such as Spark and Cloud Services. You will need to understand your part of business logic and implement it using the language supported by the base data platform 
• Develop automated data quality check to make sure right data enters the platform and verifying the results of the calculations 
• Develop an infrastructure to collect, transform, combine and publish/distribute customer data.
• Define process improvement opportunities to optimize data collection, insights and displays.
• Ensure data and results are accessible, scalable, efficient, accurate, complete and flexible 
• Identify and interpret trends and patterns from complex data sets 
• Construct a framework utilizing data visualization tools and techniques to present consolidated analytical and actionable results to relevant stakeholders. 
• Key participant in regular Scrum ceremonies with the agile teams  
• Proficient at developing queries, writing reports and presenting findings 
• Mentor junior members and bring best industry practices 

 QUALIFICATIONS 

• 5-7+ years’ experience as data engineer in consumer finance or equivalent industry (consumer loans, collections, servicing, optional product, and insurance sales) 
• Strong background in math, statistics, computer science, data science or related discipline
• Advanced knowledge one of language: Java, Scala, Python, C# 
• Production experience with: HDFS, YARN, Hive, Spark, Kafka, Oozie / Airflow, Amazon Web Services (AWS), Docker / Kubernetes, Snowflake  
• Proficient with
• Data mining/programming tools (e.g. SAS, SQL, R, Python)
• Database technologies (e.g. PostgreSQL, Redshift, Snowflake. and Greenplum)
• Data visualization (e.g. Tableau, Looker, MicroStrategy)
• Comfortable learning about and deploying new technologies and tools. 
• Organizational skills and the ability to handle multiple projects and priorities simultaneously and meet established deadlines. 
• Good written and oral communication skills and ability to present results to non-technical audiences 
• Knowledge of business intelligence and analytical tools, technologies and techniques.

Familiarity and experience in the following is a plus:  

• AWS certification
• Spark Streaming 
• Kafka Streaming / Kafka Connect 
• ELK Stack 
• Cassandra / MongoDB 
• CI/CD: Jenkins, GitLab, Jira, Confluence other related tools

Job Description

About the Role

We are seeking an experienced and hands-on Lead AI Engineer with 8-9 years of experience in developing, fine-tuning, and deploying machine learning and deep learning models, including Generative AI systems. The ideal candidate will have strong expertise in classification, anomaly detection, and time-series modeling, along with deep experience in Transformer-based architectures and modern LLM ecosystems.

This role requires technical leadership, architectural decision-making, and mentoring of AI engineers, while actively contributing to building scalable AI solutions. Expertise in model optimization, quantization, and Retrieval-Augmented Generation (RAG) pipelines is highly desirable.

Responsibilities

• Lead the design, development, and deployment of ML and deep learning models for classification, anomaly detection, forecasting, and natural language understanding tasks.
• Architect and build scalable AI and Generative AI solutions, including RAG pipelines for document search, Q&A, summarization, and enterprise knowledge systems.
• Design, train, and fine-tune deep learning models including RNNs, GRUs, LSTMs, and Transformer architectures (e.g., BERT, T5, GPT).
• Drive the fine-tuning and adaptation of large language models (LLMs) using techniques such as Supervised Fine-Tuning (SFT) and Parameter-Efficient Fine-Tuning (PEFT) methods like LoRA or QLoRA.
• Apply model optimization techniques such as quantization, pruning, and efficient inference strategies to improve latency and reduce compute and memory footprint in production systems.
• Define and implement evaluation frameworks, track model performance, monitor model drift, and drive continuous model improvement.
• Lead collaboration with data engineering, backend, platform, and DevOps teams to productionize AI solutions using scalable infrastructure and CI/CD pipelines.
• Provide technical mentorship and guidance to junior and mid-level AI engineers and contribute to best practices in ML engineering.
• Ensure clean, reproducible code, maintain experiment tracking, documentation, and version control of models and datasets.
• Stay up to date with the latest advancements in LLMs, Generative AI, and AI infrastructure, and help drive adoption of new technologies.

Required Skills & Qualifications

• 8-9 years of hands-on experience in machine learning, deep learning, or data science roles.
• Strong programming expertise in Python and ML/DL libraries such as scikit-learn, pandas, PyTorch, and TensorFlow.
• Deep understanding of machine learning algorithms, deep learning architectures, and sequence/NLP modeling techniques.
• Extensive experience with Transformer models and open-source LLM ecosystems (e.g., Hugging Face Transformers).
• Hands-on experience building Generative AI applications and RAG-based systems using frameworks such as LangChain or LlamaIndex.
• Experience with model optimization and quantization techniques (dynamic/static quantization, INT8, etc.) for efficient inference.
• Strong understanding of embeddings, vector databases, and retrieval systems (e.g., FAISS, Pinecone, Azure AI Search).
• Experience with model evaluation, monitoring, and performance optimization in production environments.
• Familiarity with containerization (Docker), experiment tracking (MLflow), and CI/CD pipelines.
• Proven ability to lead technical initiatives and mentor engineering teams.

Preferred Qualifications

• Experience fine-tuning LLMs using SFT, LoRA, or QLoRA on domain-specific datasets.
• Exposure to MLOps platforms such as SageMaker, Vertex AI, or Kubeflow.
• Experience with distributed data processing frameworks like Spark and workflow orchestration tools such as Airflow.
• Contributions to research papers, technical blogs, patents, or open-source projects in ML, NLP, or Generative AI.
• Experience designing enterprise-scale AI platforms or AI-powered products.

Job Description:
7+ years of experience as a Techno-Functional specialist supporting a finance organization with an emphasis on project management.

Must have 2-3 Project implementation and more than one support experience in Oracle EBS R12.

Expert level knowledge of Oracle Applications Framework, Oracle Workflow, Oracle Forms, Oracle Report, XML Report, PLSQL

Functional knowledge in financial module like, GL,AP, AR PO, Project is must Extensive use of oracle APIs and interfaces Experience in performance tuning of the code Experience in shell scripting.

Worked on Oracle Alert, AME, OAM ,DFF etc Good to have ADF experience Good to have ORDS experience Good to have exposure in cloud technology.

Responsibilities:
Act as a senior liaison between Business partners and IT communities Facilitate cross-functional teams through business process and application initiatives from requirements definition to prototyping, design, development, testing, training, and deployment.

Create technical designs to support business requirements.

Lead the development of technical solutions. Communicate project status and escalate issues to management. Develop and execute system test plans and scenarios.

Assist in preparing training materials for deployment of applications, modules, enhancements and bug fixes.

Assist in developing baseline datasets and reports to support testing of technical solutions.

Job description

Ruby on Rails Developer Responsibilities :

- Designing and developing new web applications.

- Maintaining and troubleshooting existing web applications.

- Writing and maintaining reliable Ruby code.

- Integrating data storage solutions.

- Creating back-end components.

- Identifying and fixing bottlenecks and bugs.

- Integrating user-facing elements designed by the front-end team.

- Connecting applications with additional web servers.

- Maintaining APIs.

Ruby on Rails Developer Requirements :

- Bachelor's degree in Computer Science, Computer Engineering, or related field.

- Experience working with Ruby on Rails as well as libraries like Resque and RSpec.

- Ability to write clean Ruby code.

- Proficiency with code versioning tools including Git, Github, SVN, and Mercurial.

Should have knowledge of web frameworks, such as Django, HTML and CSS and Python programming language.

Should have relevant work experience in coding and web development.
Good knowledge of Python and Django
Good knowledge of HTML5, CSS3 and Javascript,
Good knowledge of MY SQL database
Knowledge of Django REST framework, API.

Education Qualification- bachelor's degree in computer science, information management systems or a related field.

Work Experience - 1 to 2 years (Required)

Job Type: Full-time

Salary: ₹15,000.00 - ₹25,000.00 per month

Achieving the monthly sales target
Diligently managing the unqualified and qualified leads
Detailing their previous day work in the morning meetings
Ensuring customer on-boarding process is fast and smooth
Engaging with the existing customers to provide valuable feedback about the product