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Building the machine learning production (or MLOps) is the biggest challenge most large companies currently have in making the transition to becoming an AI-driven organization. This position is an opportunity for an experienced, server-side developer to build expertise in this exciting new frontier. You will be part of a team deploying state-of-the-art AI solutions for Fractal clients.

Responsibilities

As MLOps Engineer, you will work collaboratively with Data Scientists and Data engineers to deploy and operate advanced analytics machine learning models. You’ll help automate and streamline Model development and Model operations. You’ll build and maintain tools for deployment, monitoring, and operations. You’ll also troubleshoot and resolve issues in development, testing, and production environments.

• Enable Model tracking, model experimentation, Model automation
• Develop ML pipelines to support
• Develop MLOps components in Machine learning development life cycle using Model Repository (either of): MLFlow, Kubeflow Model Registry
• Develop MLOps components in Machine learning development life cycle using Machine Learning Services (either of): Kubeflow, DataRobot, HopsWorks, Dataiku or any relevant ML E2E PaaS/SaaS
• Work across all phases of Model development life cycle to build MLOPS components
• Build the knowledge base required to deliver increasingly complex MLOPS projects on Azure
• Be an integral part of client business development and delivery engagements across multiple domains

Required Qualifications

• 3-5 years experience building production-quality software.
• B.E/B.Tech/M.Tech in Computer Science or related technical degree OR Equivalent
• Strong experience in System Integration, Application Development or Data Warehouse projects across technologies used in the enterprise space
• Knowledge of MLOps, machine learning and docker
• Object-oriented languages (e.g. Python, PySpark, Java, C#, C++)
• CI/CD experience( i.e. Jenkins, Git hub action,
• Database programming using any flavors of SQL
• Knowledge of Git for Source code management
• Ability to collaborate effectively with highly technical resources in a fast-paced environment
• Ability to solve complex challenges/problems and rapidly deliver innovative solutions
• Foundational Knowledge of Cloud Computing on Azure
• Hunger and passion for learning new skills

Building the machine learning production System(or MLOps) is the biggest challenge most large companies currently have in making the transition to becoming an AI-driven organization. This position is an opportunity for an experienced, server-side developer to build expertise in this exciting new frontier. You will be part of a team deploying state-ofthe-art AI solutions for Fractal clients.

Responsibilities

As MLOps Engineer, you will work collaboratively with Data Scientists and Data engineers to deploy and operate advanced analytics machine learning models. You’ll help automate and streamline Model development and Model operations. You’ll build and maintain tools for deployment, monitoring, and operations. You’ll also troubleshoot and resolve issues in development, testing, and production environments.

• Enable Model tracking, model experimentation, Model automation
• Develop scalable ML pipelines
• Develop MLOps components in Machine learning development life cycle using Model Repository (either of): MLFlow, Kubeflow Model Registry
• Machine Learning Services (either of): Kubeflow, DataRobot, HopsWorks, Dataiku or any relevant ML E2E PaaS/SaaS
• Work across all phases of Model development life cycle to build MLOPS components
• Build the knowledge base required to deliver increasingly complex MLOPS projects on Azure
• Be an integral part of client business development and delivery engagements across multiple domains

Required Qualifications

• 5.5-9 years experience building production-quality software
• B.E/B.Tech/M.Tech in Computer Science or related technical degree OR equivalent
• Strong experience in System Integration, Application Development or Datawarehouse projects across technologies used in the enterprise space
• Expertise in MLOps, machine learning and docker
• Object-oriented languages (e.g. Python, PySpark, Java, C#, C++)
• Experience developing CI/CD components for production ready ML pipeline.
• Database programming using any flavors of SQL
• Knowledge of Git for Source code management
• Ability to collaborate effectively with highly technical resources in a fast-paced environment
• Ability to solve complex challenges/problems and rapidly deliver innovative solutions
• Team handling, problem solving, project management and communication skills & creative thinking
• Foundational Knowledge of Cloud Computing on Azure
• Hunger and passion for learning new skills

Responsibilities

• Design and implement advanced solutions utilizing Large Language Models (LLMs).
• Demonstrate self-driven initiative by taking ownership and creating end-to-end solutions.
• Conduct research and stay informed about the latest developments in generative AI and LLMs.
• Develop and maintain code libraries, tools, and frameworks to support generative AI development.
• Participate in code reviews and contribute to maintaining high code quality standards.
• Engage in the entire software development lifecycle, from design and testing to deployment and maintenance.
• Collaborate closely with cross-functional teams to align messaging, contribute to roadmaps, and integrate software into different repositories for core system compatibility.
• Possess strong analytical and problem-solving skills.
• Demonstrate excellent communication skills and the ability to work effectively in a team environment.

Primary Skills

• Generative AI: Proficiency with SaaS LLMs, including Lang chain, llama index, vector databases, Prompt engineering (COT, TOT, ReAct, agents). Experience with Azure OpenAI, Google Vertex AI, AWS Bedrock for text/audio/image/video modalities.
• Familiarity with Open-source LLMs, including tools like TensorFlow/Pytorch and Huggingface. Techniques such as quantization, LLM finetuning using PEFT, RLHF, data annotation workflow, and GPU utilization.
• Cloud: Hands-on experience with cloud platforms such as Azure, AWS, and GCP. Cloud certification is preferred.
• Application Development: Proficiency in Python, Docker, FastAPI/Django/Flask, and Git.
• Natural Language Processing (NLP): Hands-on experience in use case classification, topic modeling, Q&A and chatbots, search, Document AI, summarization, and content generation.
• Computer Vision and Audio: Hands-on experience in image classification, object detection, segmentation, image generation, audio, and video analysis.

• Performs implementation of high level design and specifications.
• Develops low level design, class diagrams, flow charts.
• Performs Unit testing of individually developed components and fix errors, if any
• Assist in preparation of design, technical reference & operational documentation, packaging document in collaboration with the Lead.
• Strives for technology innovation in terms of exploring new and efficient ways of writing code
• Is responsible for writing simple, reusable code by following coding standards
• Ensure proper documentation of implementation and reviews.
• Ensure timely follow ups and escalations with leads with respect to any process gaps/risks/impediments.

Role & responsibilities

• Senior Java developer with 6 to 10 years of experience having worked on Java, SpringBoot, Hibernate, Microservices, Redis, AWS S3
• Contribute to all stages of the software development lifecycle
• Design, implement, and maintain Java-based applications that can be high-volume and low-latency
• Analyze user requirements to define business objectives
• Envisioning system features and functionality
• Define application objectives and functionality
• Ensure application designs conform to business goals
• Develop and test software
• Should have good experience in Code Review
• Expecting to be 100% hands-on while working with the clients directly
• Performing requirement analysis
• Developing high-quality and detailed designs
• Conducting unit testing using automated unit test frameworks
• Identifying risk and conducting mitigation action planning
• Reviewing the work of other developers and providing feedback
• Using coding standards and best practices to ensure quality
• Communicating with customers to resolve issues
• Good Communication Skills 

Technical Lead - .NET

Responsibilities:

• Develop and deliver technical systems
• Maintain adherence to architectural standards/principles, global product-specific guidelines, usability design standards, etc.
• Participate in the development and review of documents to comply with SDLC methodologies [e.g., Engineering Work Breakdown Structure (WBS), estimation, Solution Design Document (SDD) and Software Architecture Documents (SAD)]
• Provide support and documentation to assist in sustaining the project during the transition to production where necessary
• Adhere to Application Engineering methodologies, standards, code reviews
• Provide feedback regarding application engineering methodologies, standards, and leading practices when appropriate
• Identify potential points of contention for missed activities and notify project leadership of situation and remediation plan
• Minimize technical exposure and risk on projects
• Provide technical guidance to development team members
• Technical deliverables (i.e., code and documentation) on projects assigned
• Translate detailed Requirements and Design and Solution Architecture deliverables into detailed design specifications
• Maintain effective and consistent communication within the team, with peers, the leadership team, and the peers in other IT groups
• Proactively raise issues to Technical and Group Leads when necessary
• Produce high-quality application engineering deliverables in accordance with the project timeline
• Build and unit test a project to detailed design specifications
• Provide thought leadership and technical guidance to engineering staff
• Review of code completed
• Review performance of developers
• Proactively anticipate project issues before they occur; define the problem; identify possible causes; work with the team to identify solutions; select and implement the most appropriate solution
• Apply judgment in implementing Application Engineering methodologies, processes, and practices to specific requirements of projects/programs which may include product design engineering, information security, code maintainability and reliability

Requirements:

Must Have:

• Bachelor’s OR master’s degree in a technical field and/or equivalent work experience
• At least 3 years acting a senior architecture / technical lead role in a comparable organization
• Significant experience of deploying large, enterprise-wide implementations to significant user volumes
• At least 5 years of hands-on experience leading a team of developers - defining work breakdown structures/tasks, assigning the teamwork items, monitoring, and ensuring quality and adherence to standards etc.
• At least 8 years of relevant hands-on work experience building, integrating, and delivering enterprise-wide web and windows applications using Microsoft and other technologies for large organizations on complex projects
• 8+ years of ASP.Net MVC, ASP.Net experience
• 8+ years of experience of working with applications that have a SQL Server backend
• 5+ years of experience with Object-Relational Mappers such as Entity Framework, ADO.NET, Dapper
• Expert level knowledge of .NET Web API is required. .NET Core knowledge is preferred, but Web API experience with legacy .NET is ok
• 5+ years of experience with GIT
• 3+ years of experience of Azure Devops
• In-depth knowledge of object-oriented analysis and design (OOAD) principles, and familiarity with many design patterns for Software applications.
• Demonstrated expertise in application design and construction, work breakdown structure of items, design and code reviews, unit test and build activities, deployment and performance related activities, documentation, support, and training/mentoring
• Excellent communication skills, verbal and written

Nice to have:

• Ideally experience working with SSRS, SSIS
• Experience with MongoDB or another document database would be a plus
• Knowledge and experience with working on N-Tier applications.
• Demonstrated ability to build strong working relationships
• Experience working on projects following Agile methodologies would be ideal
• Experience working with Azure or other cloud providers would be ideal
• Ability to work within diverse, global, virtual teams.
• Proven ability to thrive under pressure
• Some experience with design and prototyping tools and diagramming is desired