Technical Architect - Machine Learning

AI/ML Engineer AI Operating System for Capital Markets Location Bangalore/Chennai Experience 5+ years Function Artificial Intelligence / Machine Learning Employment Type About Transient.AI Full-time Transient.AI is building a next-generation AI Operating System for capital markets — a unified intelligence layer that connects research, trading, compliance, and sales functions at banks and hedge funds. Today, these teams largely operate on disconnected legacy systems, forcing manual, expensive workarounds. Transient.AI replaces that fragmentation with a single AI-native layer built for institutional-grade compliance, security, and auditability. The company already has live products in market, including Caddie.AI (a research automation tool that cuts hedge fund research time significantly), ClarityRIA (helping sales teams identify the right investors in seconds), and CapFlo.AI (automated parsing of complex derivatives contracts). Founded by former traders and technologists from Goldman Sachs, Credit Suisse, UBS, and McKinsey, Transient.AI is headquartered in New York, with teams in Miami, Singapore, and India. The company has raised Series A funding and is scaling its engineering and product organization globally. Role Overview Transient.AI is hiring an experienced AI/ML Engineer to join its India engineering team in Bangalore/Chennai. This is a hands-on, build-from-scratch role — you'll be designing and shipping the core machine learning systems that power the company's flagship products, working closely with founders and senior engineers rather than inheriting existing infrastructure. Key Responsibilities • Design, build, and deploy machine learning and AI models that power Transient.AI's core products (research automation, document intelligence, investor matching, and workflow orchestration). • Workonapplied NLP/LLMsystems, including retrieval-augmented generation, structured extraction from unstructured financial documents, and model evaluation pipelines. • Partner closely with product and founding engineers to translate capital markets workflows into scalable AI systems. • Ownmodelperformance, reliability, and cost — from experimentation through production deployment. • Build and maintain data pipelines, feature stores, and evaluation frameworks to support rapid iteration. • Ensuresystems meet the compliance, auditability, and security standards required in regulated financial environments. What We're Looking For • 5+years ofexperience building and deploying machine learning or AI systems in production.• Strong hands-on experience with Python and modern ML/AI frameworks (PyTorch, TensorFlow, Hugging Face, LangChain, or equivalent). • Experience with LLMs — fine-tuning, prompt engineering, RAG architectures, or agentic systems — is highly valued. • Solid grounding in data structures, distributed systems, and MLOps practices (model serving, monitoring, versioning). • Prior experience at a strong product company, high-growth startup, or a top-tier engineering background • Comfort operating in an early-stage, high-ownership environment with limited process and high ambiguity. • Exposure to fintech, capital markets, or other regulated industries is a plus, though not mandatory. WhyJoin Transient.AI • Build core AI systems from the ground up — not maintain legacy code. • Workdirectly with founders who have deep, first-hand Wall Street experience (Goldman Sachs, Credit Suisse, UBS, McKinsey). • JoinaSeries A-funded company solving a real, expensive problem for institutional finance. • Bepart ofasmall, global team with outsized ownership and impact. .

About NonStop io Technologies

NonStop io Technologies is a value-driven company with a strong focus on process-oriented software engineering. We specialize in Product Development and have a decade's worth of experience in building web and mobile applications across various domains. NonStop io Technologies follows core principles that guide its operations and believes in staying invested in a product's vision for the long term. We are a small but proud group of individuals who believe in the 'givers gain' philosophy and strive to provide value in order to seek value. We are committed to and specialize in building cutting-edge technology products and serving as trusted technology partners for startups and enterprises. We pride ourselves on fostering innovation, learning, and community engagement. Join us to work on impactful projects in a collaborative and vibrant environment.

Brief Description:

We're seeking an AI/ML Engineer to join our team. As AI/ML Engineer, you will be responsible for designing, developing, and implementing artificial intelligence (AI) and machine learning (ML) solutions to solve real-world business problems. You will work closely with engineering teams, including software engineers, domain experts, and product managers, to deploy and integrate Applied AI/ML solutions into the products that are being built at NonStop io. Your role will involve researching cutting-edge algorithms and data processing techniques, and implementing scalable solutions to drive innovation and improve the overall user experience.

Responsibilities

● Applied AI/ML engineering; Building engineering solutions on top of the AI/ML tooling available in the industry today. Eg: Engineering APIs around OpenAI

● AI/ML Model Development: Design, develop, and implement machine learning models and algorithms that address specific business challenges, such as natural language processing, computer vision, recommendation systems, anomaly detection, etc.

● Data Preprocessing and Feature Engineering: Cleanse, preprocess, and transform raw data into suitable formats for training and testing AI/ML models. Perform feature engineering to extract relevant features from the data

● Model Training and Evaluation: Train and validate AI/ML models using diverse datasets to achieve optimal performance. Employ appropriate evaluation metrics to assess model accuracy, precision, recall, and other relevant metrics

● Data Visualization: Create clear and insightful data visualizations to aid in understanding data patterns, model behaviour, and performance metrics

● Deployment and Integration: Collaborate with software engineers and DevOps teams to deploy AI/ML models into production environments and integrate them into various applications and systems

● Data Security and Privacy: Ensure compliance with data privacy regulations and implement security measures to protect sensitive information used in AI/ML processes

● Continuous Learning: Stay updated with the latest advancements in AI/ML research, tools, and technologies, and apply them to improve existing models and develop novel solutions

● Documentation: Maintain detailed documentation of the AI/ML development process, including code, models, algorithms, and methodologies for easy understanding and future reference.

Qualifications & Skills

● Bachelor's, Master's, or PhD in Computer Science, Data Science, Machine Learning, or a related field. Advanced degrees or certifications in AI/ML are a plus

● Proven experience as an AI/ML Engineer, Data Scientist, or related role, ideally with a strong portfolio of AI/ML projects

● Proficiency in programming languages commonly used for AI/ML. Preferably Python

● Familiarity with popular AI/ML libraries and frameworks, such as TensorFlow, PyTorch, scikit-learn, etc.

● Familiarity with popular AI/ML Models such as GPT3, GPT4, Llama2, BERT etc.

● Strong understanding of machine learning algorithms, statistics, and data structures

● Experience with data preprocessing, data wrangling, and feature engineering

● Knowledge of deep learning architectures, neural networks, and transfer learning

● Familiarity with cloud platforms and services (e.g., AWS, Azure, Google Cloud) for scalable AI/ML deployment

● Solid understanding of software engineering principles and best practices for writing maintainable and scalable code

● Excellent analytical and problem-solving skills, with the ability to think critically and propose innovative solutions

● Effective communication skills to collaborate with cross-functional teams and present complex technical concepts to non-technical stakeholders

Key Responsibilities

Backend Development

• Design, develop, and maintain scalable backend services using Rust, Python, and TypeScript.
• Build high-performance microservices and APIs for AI-driven products.
• Develop fault-tolerant, secure, and maintainable distributed systems.
• Design event-driven architectures and asynchronous processing pipelines.
• Implement caching, message queues, and database optimization strategies.

AI & Machine Learning Integration

• Build and maintain backend infrastructure supporting LLMs, Generative AI, RAG systems, and AI Agents.
• Integrate models from providers such as OpenAI, Anthropic, Gemini, and open-source LLMs.
• Develop vector search solutions using Pinecone, Weaviate, Qdrant, or similar technologies.
• Build AI workflows for content generation, summarization, sentiment analysis, and conversational intelligence.
• Optimize AI inference pipelines for performance and cost efficiency.

System Architecture

• Design scalable architectures capable of handling high traffic and large volumes of data.
• Develop real-time processing systems and data pipelines.
• Implement observability, monitoring, logging, and alerting mechanisms.
• Drive performance tuning and latency optimization across services.

Cloud & DevOps

• Deploy and manage applications on AWS, GCP, or Azure.
• Work with Docker, Kubernetes, CI/CD pipelines, and Infrastructure as Code.
• Ensure system reliability, security, and scalability. 

Staff Engineer - AI:

Location : India, Remote

Job Description

Egnyte is seeking an experienced Staff Software Engineer to join our Engineering department. The Engineering department builds large distributed components and services that run Egnyte's Cloud Platform. Our code serves billions of requests per day with sub-second latency in a fault-tolerant environment. We process and analyze millions of files and events daily. Some of the responsibilities for this department include Egnyte's Cloud File System, Content Classification, Content Lifecycle Management, User Behavior Analysis, Object Store, Metadata Stores, Search Systems, Recommendations Systems, Synchronization, and intelligent caching of multi-petabyte datasets. We are looking for candidates with a shared passion for building large-scale distributed systems and a keen sense for tackling complexities that come with scaling through multiple orders of magnitude.

In this role, you will (But are not limited to):

• Design and develop highly scalable and resilient cloud architecture that seamlessly integrates with on-premises systems
• Drive the team’s goals and technical direction to find and pursue technical opportunities that make Egnyte’s cloud platform more efficient
• Effectively communicate complex design and architecture details
• Understand company and industry-wide trends to help develop new technologies
• Conceptualize, develop, and implement changes that prevent key systems from becoming unreliable, under-utilized, or unsupported
• Own all aspects of critical software projects from design to implementation, QA, deployment, and monitoring

Qualifications

• BS, MS, or PhD. in Computer Science or related technical field, or equivalent practical experience
• 8-15 years of professional experience in engineering with a history of technical innovation
• Experience providing technical leadership to engineers

Bonus Qualifications (Good to Have)

• The breadth of knowledge across infrastructure domains, with the ability to reason about everything from data center machine software to database solutions to machine learning infrastructure to front-end web or mobile applications
• Demonstrated success in designing and developing large-scale, complex systems
• Expertise with multi-tenant, highly complex, cloud solutions; experience with Hybrid and/or on-premises solutions desired

About Egnyte

In a content critical age, Egnyte fuels business growth by enabling content-rich business processes, while also providing organizations with visibility and control over their content assets. Egnyte’s cloud-native content services platform leverages the industry’s leading content intelligence engine to deliver a simple, secure, and vendor-neutral foundation for managing enterprise content across business applications and storage repositories. More than 16,000 customers trust Egnyte to enhance employee productivity, automate data management, and reduce file-sharing cost and complexity. Investors include Google Ventures, Kleiner Perkins, Caufield & Byers, and Goldman Sachs. For more information, visit www.egnyte.com

Software Engineer

Position Responsibilities

You will primarily execute within defined frameworks and grow your independent scope over time. The following reflects what you will own and contribute to:

Build & Integrate

• Build and maintain AI-enabled workflows, platform integrations, and internal tools using PHP, JavaScript, Workato, and Web Services
• Develop prototypes and proofs of concept; contribute to production deployments under senior guidance
• Implement and test integrations between Deltek's support platforms and internal data systems.

Analyse & Solve

• Break down defined problems into actionable tasks; identify risks, dependencies, and edge cases before they surface in production
• Troubleshoot complex issues across the full stack and document root cause findings clearly
• Investigate stakeholder-reported issues to identify whether the problem is technical, process-related, or both.

Operate & Improve

• Follow established governance, architecture, and deployment processes; raise improvement suggestions through proper channels
• Write and maintain documentation for systems, workflows, business rules, and solution designs
• Participate actively in sprint ceremonies; manage your own tasks and flag blockers early
• Demonstrate continuous learning in AI, automation, and integration technologies — this space moves fast and curiosity is part of the job.

Nice-to-Have Skills

The following are not required for the role, but candidates with depth in any of these areas will stand out. Listed in rough order of relevance to this team's current work:

Oracle Service Cloud

Workato / iPaaS

Salesforce

Gainsight

AI / LLM integration

Snowflake

Microsoft Power BI

Microsoft Power Apps

Cloud-native development

Experience with AI tools (GitHub Copilot, LLM APIs, automation agents) used in an operational or product context — not just personal experimentation — is a genuine plus for this team.

Qualifications

• Education: Bachelor's degree in Computer Science, Information Technology, Engineering, or a related technical discipline. Equivalent practical experience considered.
• Experience: 2–4 years of hands-on experience in software engineering, systems integration, or a closely related field. Internship and co-op experience counts if it involved real production systems.
• Coding: Demonstrable PHP and/or JavaScript experience — a portfolio, GitHub profile, or code sample you can speak to will strengthen your application.
• Collaboration model: Comfortable working remotely with distributed teams. The role requires regular overlap with US East/Central time zones (approximately 2:00 PM – 11:00 PM IST for at least part of the week).
• Language: Strong written and spoken English is essential — much of the collaboration with stakeholders and senior engineers happens asynchronously in writing.

🚨 We’re Building a “Top 1% Engineering Org”

We’re building a high-talent-density, AI-first R&D organization from scratch — inside a publicly listed company undergoing a full-scale transformation.

Think:

→ Rewriting legacy systems into AI-native architectures

→ Embedding LLMs + Agentic AI into core workflows

→ Reimagining platforms, infra, and data systems for the next decade

This is the kind of shift you’d expect from Google, Microsoft, or Meta —

Except you get to build it from day 0 → scale it globally.

About the Role / Team

We are building a next-generation AI-first R&D organization in Bengaluru, focused on solving complex problems across LLMs, Agentic AI systems, distributed computing, and enterprise-scale architectures.

This initiative is part of a publicly listed global company investing heavily in AI-driven transformation, re-architecting its platforms into intelligent, autonomous systems powered by large language models, workflows, and decision engines.

You will be working on:

• Agentic AI systems & LLM-powered workflows
• Distributed, scalable backend systems
• Enterprise-grade AI platforms
• Automation-first engineering environments

🚀 The Mandate

Own and evolve the technical backbone of an AI-first enterprise platform.

You will define architecture across LLM-powered systems, distributed services, and data platforms — and lead critical transformations from legacy → AI-native systems.

🧩 What You’ll Do

• Architect large-scale distributed systems powering AI-driven workflows
• Lead 0→1 and 1→N platform builds (LLM integrations, agentic systems, orchestration layers)
• Redesign legacy systems into scalable, modular, AI-native architectures
• Drive system design excellence across teams (APIs, infra, observability, reliability)
• Make high-stakes decisions on trade-offs (latency, cost, scalability, model performance)
• Mentor senior engineers and influence engineering culture/org standards
• Partner with product, data, and leadership on long-term technical strategy

🧠 What We’re Looking For

• Proven track record building high-scale backend or platform systems
• Deep expertise in distributed systems, microservices, cloud (AWS/GCP/Azure)
• Strong exposure to data systems/infra / Data / real-time architectures
• Experience or strong interest in LLMs, GenAI, or AI system design
• Exceptional system design, abstraction, and problem-solving ability
• High ownership mindset — you think in terms of systems, not tickets
• Strong coding skills in Python / Java / Go / Node.js
• Solid understanding of data structures, system design basics, and backend architecture
• Experience building scalable APIs and services
• Familiarity or curiosity around AI/LLMs, async systems, or event-driven design
• Strong debugging, problem-solving, and ownership mindset
• Solve hard system problems (latency, scale, reliability)
• Drive cross-team technical decisions and standards
• Mentor senior engineers and influence org-wide architecture 
• Design large-scale distributed systems and backend platforms
• Mentorship & Technical Leadership 
• Expertise in system design, scalability, and performance optimization

Nice to Have

• Experience integrating LLMs, vector databases, or AI pipelines
• Contributions to architecture at scale
• Experience with Agentic AI / LLM orchestration frameworks
• Background in product engineering or platform companies
• Exposure to global-scale systems (millions of users / high throughput)

🔥 What Sets You Apart

• Built platforms used by millions of users / high-throughput systems
• Experience with event-driven systems, stream processing, or infra platforms
• Prior work on AI/ML platforms, model serving, or intelligent systems

Job Overview:

We are looking for a skilled Senior Backend Engineer to join our team. The ideal candidate will have a strong foundation in Java and Spring, with proven experience in building scalable microservices and backend systems. This role also requires familiarity with automation tools, Python development, and working knowledge of AI technologies.

Responsibilities:

• Design, develop, and maintain backend services and microservices.
• Build and integrate RESTful APIs across distributed systems.
• Ensure performance, scalability, and reliability of backend systems.
• Collaborate with cross-functional teams and participate in agile development.
• Deploy and maintain applications on AWS cloud infrastructure.
• Contribute to automation initiatives and AI/ML feature integration.
• Write clean, testable, and maintainable code following best practices.
• Participate in code reviews and technical discussions.

Required Skills:

• 4+ years of backend development experience.
• Strong proficiency in Java and Spring/Spring Boot frameworks.
• Solid understanding of microservices architecture.
• Experience with REST APIs, CI/CD, and debugging complex systems.
• Proficient in AWS services such as EC2, Lambda, S3.
• Strong analytical and problem-solving skills.
• Excellent communication in English (written and verbal).

Good to Have:

• Experience with automation tools like Workato or similar.
• Hands-on experience with Python development.
• Familiarity with AI/ML features or API integrations.
• Comfortable working with US-based teams (flexible hours).

Full-Stack Machine Learning Engineer

Role: Full-Time, Long-Term Required: Python Preferred: C++

OVERVIEW

We are seeking a versatile ML engineer to join as a core member of our technical team. This is a long-term position for someone who wants to build sophisticated production systems and grow with a small, focused team. You will work across the entire stack—from data ingestion and feature engineering through model training, validation, and deployment.

The ideal candidate combines strong software engineering fundamentals with deep ML expertise, particularly in time series forecasting and quantitative applications. You should be comfortable operating independently, making architectural decisions, and owning systems end-to-end.

CORE TECHNICAL REQUIREMENTS

Python (Required): Professional-level proficiency writing clean, production-grade code—not just notebooks. Deep understanding of NumPy, Pandas, and their performance characteristics. You know when to use vectorized operations, understand memory management for large datasets, and can profile and optimize bottlenecks. Experience with async programming and multiprocessing is valuable.

Machine Learning (Required): Hands-on experience building and deploying ML systems in production. This goes beyond training models—you understand the full lifecycle: data validation, feature engineering, model selection, hyperparameter optimization, validation strategies, monitoring, and maintenance.

Specific experience we value: gradient boosting frameworks (LightGBM, XGBoost, CatBoost), time series forecasting, probabilistic prediction and uncertainty quantification, feature selection and dimensionality reduction, cross-validation strategies for non-IID data, model calibration.

You should understand overfitting deeply—not just as a concept but as something you actively defend against through proper validation, regularization, and architectural choices.

Data Pipelines (Required): Design and implement robust pipelines handling real-world messiness: missing data, late arrivals, schema changes, upstream failures. You understand idempotency, exactly-once semantics, and backfill strategies. Experience with workflow orchestration (Airflow, Prefect, Dagster) expected. Comfortable with ETL/ELT patterns, incremental vs full recomputation, data quality monitoring, database design and query optimization (PostgreSQL preferred), time series data at scale.

C++ (Preferred): Experience valuable for performance-critical components. Writing efficient C++ and interfacing with Python (pybind11, Cython) is a significant advantage.

HIGHLY DESIRABLE: MULTI-AGENT ORCHESTRATION

We are building systems leveraging LLM-based automation. Experience with multi-agent frameworks highly desirable: LangChain, LangGraph, or similar agent frameworks; designing reliable AI pipelines with error handling and fallbacks; prompt engineering and output parsing; managing context and state across agent interactions. You do not need to be an expert, but genuine interest and hands-on experience will set you apart.

DOMAIN EXPERIENCE: FINANCIAL DATA AND CRYPTO

Preference for candidates with experience in quantitative finance, algorithmic trading, or fintech; cryptocurrency markets and their unique characteristics; financial time series data and forecasting systems; market microstructure, volatility, and regime dynamics. This helps you understand why reproducibility is non-negotiable, why validation must account for temporal structure, and why production reliability cannot be an afterthought.

ENGINEERING STANDARDS

Code Quality: Readable, maintainable code others can modify. Proper version control (meaningful commits, branches, code review). Testing where appropriate. Documentation: docstrings, READMEs, decision records.

Production Mindset: Think about failure modes before they happen. Build in observability: logging, metrics, alerting. Design for reproducibility—same inputs produce same outputs.

Systems Thinking: Consider component interactions, not just isolated behavior. Understand tradeoffs: speed vs accuracy, flexibility vs simplicity. Zoom between architecture and implementation.

WHAT WE ARE LOOKING FOR

Self-Direction: Given a problem and context, you break it down, identify the path forward, and execute. You ask questions when genuinely blocked, not when you could find the answer yourself.

Long-Term Orientation: You think in years, not months. You make decisions considering future maintainability.

Intellectual Honesty: You acknowledge uncertainty and distinguish between what you know versus guess. When something fails, you dig into why.

Communication: You explain complex concepts clearly and document your reasoning.

EDUCATION

University degree in a quantitative/technical field preferred: Computer Science, Mathematics, Statistics, Physics, Engineering. Equivalent demonstrated expertise through work also considered.

TO APPLY

Include: (1) CV/resume, (2) Brief description of a production ML system you built, (3) Links to relevant work if available, (4) Availability and timezone.