Project description
We're seeking a passionate and skilled Machine Learning Engineer to join our growing team in Hyderabad. You'll play a key role in designing, developing, and deploying scalable ML solutions in Capital Markets. This is a fantastic opportunity to work with cutting-edge technologies and contribute to impactful projects in a collaborative, innovation-driven environment.
Responsibilities
Design and implement robust machine learning models using modern frameworks and libraries.Collaborate with data scientists, engineers, and stakeholders to translate business requirements into technical solutions.Optimize and deploy models using tools like TensorFlow Serving, TorchServe, ONNX, and TensorRT.Build and manage ML pipelines using MLflow, Kubeflow, and AWS ML pipelines.Work with large-scale data using PySpark and integrate models into production environments.Monitor model performance and retrain as needed to ensure accuracy and efficiency.Collaborate with cross-functional teams to integrate AI solutions into scalable productsEnsure best practices in data engineering and contribute to architectural decisionsContribute to the mentoring and development of junior team members.Support senior team members in identifying and addressing data science opportunities.Mandatory skills
Strong proficiency in Python and ML libraries such as:pandas, NumPy, scikit-learnXGBoost, LightGBM, CatBoostTensorFlow, Keras, PyTorchExperience with model deployment and serving tools:ONNX, TensorRT, TensorFlow Serving, TorchServeFamiliarity with ML lifecycle tools:MLflow, Kubeflow, Azure ML PipelinesExperience working with distributed data processing using PySpark.Solid understanding of software engineering principles and version control (e.g., Git).Excellent problem-solving skills and ability to work independently or in a team.Typically, 6+ years of relevant work experience in industry, with a minimum of 2+ years in a similar role.Proficiencies in data cleansing, exploratory data analysis, and data visualizationContinuous learner that stays abreast with industry knowledge and technologyNice to have skills
Previous experience in Capital Markets software development projects Read LessProject Description:
We are seeking a Senior Semantic Engineer to implement semantic data frameworks that provide a shared structure for enterprise data. In this role you will focus on building and maintaining ontologies and knowledge graphs, enforcing semantic validation rules for data quality, and collaborating with AI teams to integrate these semantic structures into intelligent applications. The position is industry-agnostic, emphasizing strong semantic web expertise and the ability to apply it in any enterprise context.
Responsibilities:
• Ontology Design & Maintenance: Design, develop, and maintain ontologies (using OWL/RDF or similar) that model key enterprise data domains and relationships, ensuring a consistent and shared data vocabulary across the organization. This includes collaborating with domain experts to capture real-world concepts and validate that the ontology accurately represents business knowledge.
• Knowledge Graph Development: Build and manage enterprise knowledge graphs based on the defined ontologies, linking diverse data sources into a unified graph data model. This involves configuring graph databases or triple stores, populating the knowledge graph with data (RDF triples), and optimizing it for query performance and scalability.
• Semantic Querying (SPARQL): Create and optimize SPARQL queries to enable efficient retrieval, integration, and analysis of data from the knowledge graph. You will develop semantic queries and endpoints that support advanced search and analytics use cases, making it easier for others to retrieve insights from linked data.
• Validation Rules & Data Quality: Implement semantic validation rules and consistency checks (e.g., using SHACL or OWL constraints) to ensure data integrity and quality within the ontology and knowledge graph. You will define and enforce data modelling conventions and business rules so that enterprise data conforms to the ontology's standards and remains interoperable across systems.
• Integration with Enterprise Systems: Work closely with software engineers, data architects, and IT teams to integrate the ontology and knowledge graph into the organization's existing data infrastructure and workflows. This includes embedding semantic models in data pipelines, APIs, and databases, so that enterprise applications can produce and consume linked data seamlessly.
• Collaboration & Cross-Functional Support: Collaborate with cross-functional teams and stakeholders. For example, partner with AI/ML teams to incorporate the knowledge graph into AI-driven solutions, and team up with business analysts or data stewards to align the semantic models with business needs. You will communicate semantic concepts to non-technical stakeholders, providing training or documentation to ensure adoption of the semantic framework across the organisation.
• Integration with AI Agents: Work with AI agents and large language model (LLM) teams to leverage the ontology and knowledge graph for intelligent applications. For instance, you might enable an AI chatbot to use the knowledge graph for more context-aware responses, or develop mechanisms for AI systems to perform reasoning over the ontologies. This responsibility ensures that semantic data structures enhance AI initiatives (e.g. improving context, disambiguation, and knowledge retrieval in AI workflows).
• Standards & Best Practices: Stay current with emerging semantic web standards, tools, and best practices. Continuously improve the semantic architecture by adopting relevant metadata standards and ensuring alignment with industry best practices for ontologies and knowledge graphs. You will also contribute to establishing internal guidelines and best practices for semantic data management, promoting a culture of well-structured, semantically-rich data across the enterprise.
Mandatory Skills Description:
Ontology Design & Maintenance: Design, develop, and maintain ontologies (using OWL/RDF or similar).
Semantic Web Proficiency: Strong knowledge of semantic web technologies and standards - specifically, hands-on proficiency with OWL (Web Ontology Language) and RDF (Resource Description Framework) for ontology modelling, as well as SPARQL for querying graph data.
Knowledge Graph Experience: Practical experience building or maintaining knowledge graphs or linked data systems in an enterprise setting.
Data Modelling & Integration Skills: A solid understanding of data modelling principles, data architecture, and integrating heterogeneous data sources. You should be capable of abstracting real-world entities into a semantic schema and mapping relational or NoSQL data to an ontology.
Programming Skills: Proficiency in at least one programming or scripting language (such as Python, Java, or similar)
Nice-to-Have Skills Description:
• Metadata Standards: Familiarity with metadata standards and vocabularies such as Dublin Core, schema.org, or other industry-specific ontologies/taxonomies. Experience applying these standards to annotate or integrate data
• AI and LLM Integration: Experience working on projects that involve AI agents or large language models, where ontologies or knowledge graphs were used to improve AI performance.
• Enterprise System Integration: Proven experience integrating semantic technologies into existing enterprise systems or data platforms.
• Tools & Platforms: Hands-on experience with ontology and knowledge graph tools is beneficial.
Languages:
English: C1 Advanced
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We are developing an advanced Capital Markets analytical platform powered by Agentic AI, focused on intelligent workflows, autonomous analysis, and decision support rather than traditional chart-heavy visualization. We're looking for a Senior React Developer to help design and build intuitive, high impact user experiences on top of cutting edge AI capabilities.
This role is ideal for someone who enjoys working on complex, logic driven interfaces, orchestrating AI-driven interactions, and turning sophisticated financial intelligence into usable products.
Responsibilities:
• Build and maintain complex frontend applications using React and TypeScript
• Develop UI flows that support Agentic AI workflows (task orchestration, recommendations, reasoning steps, human in the loop controls)
• Implement conversational, action driven, and form based interfaces for analytical and decision-support use cases
• Work closely with AI/ML engineers, backend developers, and product managers to integrate AI agents into the product
• Translate complex analytical and financial requirements into clear, efficient user experiences
• Ensure performance, reliability, and scalability of frontend systems
• Contribute to frontend architecture, technical standards, and code quality
• Mentor other engineers and participate in code reviews and design discussions
Mandatory Skills Description:
• 5+ years of professional frontend development experience with React.
• Strong hands-on experience with React, modern JavaScript (ES6+), and TypeScript
• Solid understanding of state management and async workflows (Redux, React Query, Zustand, etc.)
• Experience building logic heavy, data driven, or workflow oriented applications
• Comfortable working with AI powered features (LLMs, agent orchestration, decision engines, or rule based systems)
• Strong knowledge of HTML, CSS, and frontend performance optimization
• Experience integrating frontend applications with REST APIs and/or GraphQL
Nice-to-Have Skills Description:
Exposure to Capital Markets, trading, financial analytics, or risk systems
Languages:
English: B2 Upper Intermediate
Read LessProject Description:
We are seeking a skilled TDM Engineer with practical experience in the Delphix DataOps platform. The role entails managing test data environments, ensuring compliance with data privacy regulations, and facilitating efficient data provisioning for development and testing teams.
Responsibilities:
Configure, manage, and optimise data virtualisation environments for data masking and provisioning.Create, refresh, and maintain test data sets across multiple environments to support testing needs.Implement data masking strategies to protect sensitive information in compliance with regulatory frameworks such as GDPR and HIPAA.Design and maintain synthetic datasets for use cases where production data is unavailable or unsuitable.Integrate data virtualisation tools with CI/CD pipelines to accelerate test cycles and enhance efficiency.Monitor and optimise data virtualisation performance to ensure speed and reliability.Collaborate with QA, DevOps, and application teams to ensure timely delivery of test data.Document processes, configurations, and best practices to support operational consistency.Mandatory Skills Description:
8+ years in Test Data Management, with at least 3+ years of hands-on Delphix expertise.Bachelor's degree in Computer Science, Information Technology, or related discipline.Practical expertise in Delphix DataOps, including data masking and virtualisation techniques.Comprehensive understanding of test data management methodologies and associated tools.Proficient in programming and scripting languages such as SQL, Python, and Shell to automate processes.Familiar with cloud platforms-AWS, Azure, GCP-and CI/CD tools like Jenkins, GitLab, and Azure DevOps.Experienced in managing and working with relational databases including Oracle, SQL Server, and PostgreSQL.Knowledgeable about data privacy regulations and governance standards relevant to compliance.Ability to apply technical knowledge to optimise data operations within complex environments.Effective at integrating automation and cloud-based solutions to enhance workflow efficiency.Skilled in maintaining compliance through adherence to data governance practices.Nice-to-Have Skills Description:
Experience with synthetic data generation tools: Optional familiarity with tools that create artificial data sets for testing and development purposes.Knowledge of data governance frameworks: An understanding of principles and policies to manage data availability, usability, integrity, and security.Exposure to containerization technologies (Docker, Kubernetes): Basic experience with container platforms for application deployment and management.Familiarity with regulatory audits in BFSI: Optional awareness of compliance and audit processes within the banking, financial services, and insurance sectors. Read LessProject description
We are looking for an experienced SAP FICO Business Relationship Manager (BRM) to join our growing enterprise application team. In this role, you will bridge the gap between business requirements and technical SAP configurations, driving end-to-end implementations, enhancements, and global rollouts. You will be responsible for scoping new requirements, delivering accurate effort estimations, and ensuring the architectural integrity of our global SAP financial footprint across core FI/CO modules, banking systems, and localized ledger reporting.
Responsibilities
-Business Alignment & Estimation: Partner with business stakeholders to assess complex requirements, translate them into robust functional designs, and provide accurate resource/timeline estimations for new developments.-Enterprise Architecture: Design, configure, and maintain the SAP Enterprise Structure, ensuring seamless setup and initialization of new company codes globally.-Financial & Controlling Configuration: Execute end-to-end configurations across General Ledger (GL), Accounts Payable (AP), Accounts Receivable (AR), Asset Accounting (FI-AA), and Controlling (CO).-Banking & Cash Management: Design and maintain electronic banking infrastructures, optimizing automated payment processes and bank statement processing.-Intercompany & Ledger Management: Manage complex intercompany posting matrices and multi-ledger frameworks to support parallel accounting and statistical reporting requirements.-System Integrity & Governance: Maintain custom configuration elements, design validations/substitutions, and manage custom table architectures.-Documentation: Author, review, and maintain high-quality functional specification documents (FSDs), configuration rationales, and system blueprints.Mandatory skills
Project Implementation: Proven experience in end-to-end lifecycles and providing requirement estimations.Enterprise Structure: Hands-on configuration of organizational units, specifically setting up new Company Codes.General Ledger (GL): Master data, transactional processing, reconciliation, tax codes, and Financial Statement Version (FSV).Accounts Payable (AP): Vendor master, account groups, FBZP configuration, and payment mediums (DMEE, OBPM4, OBPM3).Banking: Bank master data, bank determination, EBS setup (OT83), and search strings (OTPM).Asset Accounting (FI-AA): Configuration for new company codes, master data (AS01), depreciation/acquisitions, and account determination (OA90).Accounts Receivable (AR): Customer master data, invoicing structures, and payment clearings.Controlling (CO): Cost Center and Profit Center accounting, assessment cycles, and default account assignments (OKB9).Intercompany Postings: Clear execution of intercompany clearing configurations via OBYA.Ledgers: Understanding and application of leading, local, and statistical ledger architectures.Advanced FI Configurations: Technical setup of validations (GGB0), substitutions (GGB1), custom table updates (SM30), and sets (GS01/GS02).Documentation Excellence: Writing functional specifications for ABAP developments and configuration logs. Read LessProject description
We are looking for an experienced SAP FICO Business Relationship Manager (BRM) to join our growing enterprise application team. In this role, you will bridge the gap between business requirements and technical SAP configurations, driving end-to-end implementations, enhancements, and global rollouts. You will be responsible for scoping new requirements, delivering accurate effort estimations, and ensuring the architectural integrity of our global SAP financial footprint across core FI/CO modules, banking systems, and localized ledger reporting.
Responsibilities
-Business Alignment & Estimation: Partner with business stakeholders to assess complex requirements, translate them into robust functional designs, and provide accurate resource/timeline estimations for new developments.-Enterprise Architecture: Design, configure, and maintain the SAP Enterprise Structure, ensuring seamless setup and initialization of new company codes globally.-Financial & Controlling Configuration: Execute end-to-end configurations across General Ledger (GL), Accounts Payable (AP), Accounts Receivable (AR), Asset Accounting (FI-AA), and Controlling (CO).-Banking & Cash Management: Design and maintain electronic banking infrastructures, optimizing automated payment processes and bank statement processing.-Intercompany & Ledger Management: Manage complex intercompany posting matrices and multi-ledger frameworks to support parallel accounting and statistical reporting requirements.-System Integrity & Governance: Maintain custom configuration elements, design validations/substitutions, and manage custom table architectures.-Documentation: Author, review, and maintain high-quality functional specification documents (FSDs), configuration rationales, and system blueprints.Mandatory skills
Project Implementation: Proven experience in end-to-end lifecycles and providing requirement estimations.Enterprise Structure: Hands-on configuration of organizational units, specifically setting up new Company Codes.General Ledger (GL): Master data, transactional processing, reconciliation, tax codes, and Financial Statement Version (FSV).Accounts Payable (AP): Vendor master, account groups, FBZP configuration, and payment mediums (DMEE, OBPM4, OBPM3).Banking: Bank master data, bank determination, EBS setup (OT83), and search strings (OTPM).Asset Accounting (FI-AA): Configuration for new company codes, master data (AS01), depreciation/acquisitions, and account determination (OA90).Accounts Receivable (AR): Customer master data, invoicing structures, and payment clearings.Controlling (CO): Cost Center and Profit Center accounting, assessment cycles, and default account assignments (OKB9).Intercompany Postings: Clear execution of intercompany clearing configurations via OBYA.Ledgers: Understanding and application of leading, local, and statistical ledger architectures.Advanced FI Configurations: Technical setup of validations (GGB0), substitutions (GGB1), custom table updates (SM30), and sets (GS01/GS02).Documentation Excellence: Writing functional specifications for ABAP developments and configuration logs. Read Less