As part of our team, youll be tasked with handling substantial datasets to develop machine learning models catering to our enterprise clients. Your role will also involve contributing to the development of foundational models for our product. To excel in this position, you should possess a strong analytical aptitude, with a deep understanding of data analysis, mathematics, and statistics. Critical thinking and problem-solving abilities are imperative for the interpretation of data. Furthermore, we value a genuine enthusiasm for machine learning and a commitment to research. Responsibilities: Develop and Deploy predictive models in production and conduct advanced analytics, data mining, and data visualization to influence strategic decisions Architect and build data models to transform data into insights at scale Evaluate model performance and conduct iterative model training to maximize predictive and forecast accuracy on an on-going basis. Requirements: Bachelor or above degree in Computer Science, Applied Mathematics, Statistics, Econometrics, or related field 4-6 years of work experience depending on educational level and relevance Sharp analytical abilities and problem solving skills Working knowledge of Statistics, programming and predictive modeling Expert knowledge of Python or a related scripting language, familiarity with Python packages such as pandas, numpy, scipy, nltk is a must. Databricks Spark are good to have Comfort manipulating and analyzing complex, high-volume, high dimensionality data coming from various data sources Experience working with databases like MySQL, NoSQL, MongoDB, SQL Server, Oracle or Teradata.

The Software Engineer - SDET is responsible for delivering high-quality software through advanced automated testing strategies. This role includes overseeing the creation and execution of robust testing frameworks, working closely with development teams to integrate testing practices seamlessly into the software development lifecycle, and leading efforts to enhance and optimize testing processes and methodologies. This role also drives innovation in testing tools and techniques, ensures that testing standards are met, and contributes to the overall quality assurance strategy of the organization. Responsibilities Design, develop, and implement scalable test automation frameworks and tools that align with the organization s testing requirements and goals Work with engineers and product managers to design test plans and scripts for verifying software functionality, performance, and security Stay current with industry trends, emerging technologies, and best practices and recommend tools to enhance testing and product quality Monitor test results, analyze defect trends, and provide actionable insights for product improvements Drive continuous improvement in the testing processes, tools, and methodologies to enhance software quality and development efficiency Document test cases, scripts, results, and metrics on coverage, defects, and performance Requirements Bachelor s degree in Computer Science, Engineering, or a related field with 5-7 years of experience in software development and test automation. Proficiency in programming languages (e.g., JavaScript, Python and SQL) Experience with test automation tools (e.g., Selenium, Cypress, JUnit, TestNG, pytest) and CI/CD tools - Jenkins, Bit bucket, Github, CircleCi Strong understanding of software development methodologies (e.g., Agile, Scrum) Familiarity with performance testing and security testing tools Exceptional problem-solving and analytical skills, combined with strong leadership and mentoring abilities

As a key member of our data platform team, youll lead the development of our next-gen cutting-edge data platform. Your responsibilities will include building robust data pipelines for data acquisition, processing, and implementing optimized data models, creating APIs and data products to support our machine learning models, insights engine, and customer-facing applications. Additionally, youll harness the power of GenAI throughout the data platform lifecycle, while maintaining a strong focus on data governance to uphold timely data availability with high accuracy. What we re looking for Bachelors degree or higher in Computer Science, Engineering or related field with 13+ years of experience in data engineering with a strong focus on designing and building scalable data platforms and products Proven expertise in data modeling, ETL/ELT processes, data warehousing with distributed computing - Hadoop, Spark and Kafka Proficient in programming languages such as Python, Java and SQL Experience with cloud such as AWS, Azure or GCP and related services (S3, Redshift, BigQuery, Dataflow) Strong understanding of SQL / NoSQL databases (e.g. Postgres, MySQL, Cassandra) Proven expertise in data quality checks to ensure data accuracy, completeness, consistency, and timeliness Excellent problem-solving in fast-paced, collaborative environment, coupled with strong communication for effective interaction with tech non-tech stakeholders

Design and deploy scalable, high-performance technology solutions across various domains, including backend, frontend, data platforms etc and establish and maintain architectural standards for reliability, security, and performance Lead and mentor engineering teams across multiple disciplines and provide technical guidance and support, and promote best practices in coding, testing, and deployment processes. Enhance systems / processes to achieve optimal performance, scalability, and maintainability. Address and resolve complex technical issues to ensure overall system reliability Work closely with product managers, engineers, and other stakeholders to define system requirements and deliver integrated solutions that meet business and technical needs Stay abreast of industry trends and emerging technologies to integrate new tools and techniques across various technology stacks. Continuously refine architecture and development practices to drive innovation and efficiency Manage the lifecycle of projects spanning multiple technology areas, ensuring timely delivery, high quality, and alignment with architectural goals. Effectively manage technical debt and make strategic decisions to maintain project momentum Create and maintain detailed documentation of architectural designs and decisions across technology domains. Facilitate knowledge sharing and communication to support development and troubleshooting Requirements Bachelor s degree in Computer Science or related field with 17+ years of experience, including 4+ years in a principal or architectural role Deep expertise in designing and implementing scalable and distributed systems Expertise in programming languages and frameworks (e.g., Python, Node.js, Java) Strong knowledge of database systems (e.g., SQL, NoSQL), RESTful APIs, and microservices architecture Strong knowledge of software design patterns, architectural frameworks, data pipelines, data modeling, and best practices Proficiency in cloud platforms (e.g., AWS, Azure, Google Cloud) and containerization (e.g., Docker, Kubernetes) Strong problem-solving, analytical, and leadership skills, with the ability to collaborate with cross-functional teams and communicate technical concepts effectively Familiarity with DevOps practices, CI/CD pipelines and emerging technologies (e.g., GenAI, AI/ML)

Lead the development and scaling of accounting operations, ensuring alignment with US GAAP while managing India entity accounting in full compliance with Indian GAAP. Manage all financial operations and systems, including A/P, A/R, reconciliations, and month-end closing, while continuously optimizing processes for efficiency. Establish and strengthen financial controls, policies, and procedures, adapting them as the company grows to ensure robust operations and compliance. Work closely with external auditors and tax professionals to ensure cross-border compliance for both US and India operations. Tax, Compliance Audit Management Partner with US tax teams to oversee cross-border tax filings and manage compliance with global tax regulations. Ensure full compliance with Indian tax laws (GST, TDS, corporate tax) and manage statutory audits and regulatory filings for both entities. Oversee all compliance activities, ensuring both Indian and US operations meet evolving regulatory requirements. Team Leadership Benefits Operations Oversee payroll processing and coordinate with global payroll providers to ensure compliance with labor laws and company policies. Manage Payroll and benefits administration in India, ensuring compliance with local labor laws while fostering a positive employee experience. Supervise outsourced finance, payroll benefits functions supporting the US parent company, managing growth as the business scales. Building Scalable Accounting Infrastructure Design and implement scalable accounting systems, tools, and processes to support the company s rapid growth. Create and optimize financial reporting frameworks, ensuring data accuracy, timely decision-making, and scalability as the business expands. Establish best practices and build a strong foundation for future accounting needs, anticipating the evolving demands of the organization. Strategic Financial Insights Decision Support Provide leadership with actionable financial insights to drive data-driven decisions as the India operations scale. Act as a strategic business partner, ensuring seamless communication and collaboration between finance operations across the US and India. Requirements Chartered Accountant (CA) with 10+ years of relevant experience. Experience working with high-growth US-based startups and managing financial operations for global entities. Deep expertise in US and Indian GAAP, with proven hands-on experience in A/P, A/R, reconciliations, month-end close, and financial controls. Experience managing cross-border tax compliance and global audits. Proven ability to build scalable accounting infrastructure and processes in a fast-growing company. A strong track record of leading and developing high-performing teams. Ability to thrive in a dynamic startup environment, balancing tactical execution and long-term strategic planning.

Develop and Deploy predictive models in production and conduct advanced analytics, data mining, and data visualization to influence strategic decisions Architect and build data models to transform data into insights at scale Evaluate model performance and conduct iterative model training to maximize predictive and forecast accuracy on an on-going basis. Stay up to date with the latest advancements in AI/ML and GenAI, and drive innovation by evaluating new methodologies, architectures, and tools. Optimize data infrastructure and implement MLOps best practices to automate training, monitoring, and deployment of ML models. Collaborate with engineering teams to integrate AI models into production systems, ensuring scalability, security, and operational efficiency. Requirements: Bachelor or above degree in Computer Science, Applied Mathematics, Statistics, Econometrics, or related field 10+ years of industry experience in data science, machine learning, advanced analytics, with a proven track record of leading impactful projects. Exceptional analytical and problem-solving skills, with the ability to break down complex business challenges into data-driven solutions. Deep expertise in statistical modeling, machine learning, and predictive analytics, with hands-on experience deploying models at scale. Strong programming skills in Python (or similar languages) and extensive experience with libraries such as pandas, numpy, scipy, and scikit-learn Experience with big data frameworks like Spark and Databricks, including optimization for large-scale data processing. Proficiency in working with large, high-dimensional datasets, integrating multiple data sources, and deriving meaningful insights. Expertise in Generative AI (GenAI), including LLMs, transformer architectures (GPT, BERT, T5, etc.), and diffusion models (Good to have) Experience with cloud platforms (AWS, Azure, or GCP) and working knowledge of ML model deployment (MLOps) and AI/ML lifecycle management Proficiency in databases, including SQL (MySQL, SQL Server, PostgreSQL), NoSQL (MongoDB, Cassandra), or data warehouses (Snowflake, BigQuery, Redshift). Strong leadership skills, with experience mentoring junior data scientists and collaborating cross-functionally with product, engineering, and business teams. Ability to communicate technical concepts to non-technical stakeholders and drive data-informed decision-making across the organization