Technical Architect - Machine Learning

Job Title: AI/ML Engineer – Voice (2–3 Years)

Location: Bengaluru (On-site)

Employment Type: Full-time

About Impacto Digifin Technologies

Impacto Digifin Technologies enables enterprises to adopt digital transformation through intelligent, AI-powered solutions. Our platforms reduce manual work, improve accuracy, automate complex workflows, and ensure compliance—empowering organizations to operate with speed, clarity, and confidence.

We combine automation where it’s fastest with human oversight where it matters most. This hybrid approach ensures trust, reliability, and measurable efficiency across fintech and enterprise operations.

Role Overview

We are looking for an AI Engineer Voice with strong applied experience in machine learning, deep learning, NLP, GenAI, and full-stack voice AI systems.

This role requires someone who can design, build, deploy, and optimize end-to-end voice AI pipelines, including speech-to-text, text-to-speech, real-time streaming voice interactions, voice-enabled AI applications, and voice-to-LLM integrations.

You will work across core ML/DL systems, voice models, predictive analytics, banking-domain AI applications, and emerging AGI-aligned frameworks. The ideal candidate is an applied engineer with strong fundamentals, the ability to prototype quickly, and the maturity to contribute to R&D when needed.

This role is collaborative, cross-functional, and hands-on.

Key Responsibilities

Voice AI Engineering

• Build end-to-end voice AI systems, including STT, TTS, VAD, audio processing, and conversational voice pipelines.
• Implement real-time voice pipelines involving streaming interactions with LLMs and AI agents.
• Design and integrate voice calling workflows, bi-directional audio streaming, and voice-based user interactions.
• Develop voice-enabled applications, voice chat systems, and voice-to-AI integrations for enterprise workflows.
• Build and optimize audio preprocessing layers (noise reduction, segmentation, normalization)
• Implement voice understanding modules, speech intent extraction, and context tracking.

Machine Learning & Deep Learning

• Build, deploy, and optimize ML and DL models for prediction, classification, and automation use cases.
• Train and fine-tune neural networks for text, speech, and multimodal tasks.
• Build traditional ML systems where needed (statistical, rule-based, hybrid systems).
• Perform feature engineering, model evaluation, retraining, and continuous learning cycles.

NLP, LLMs & GenAI

• Implement NLP pipelines including tokenization, NER, intent, embeddings, and semantic classification.
• Work with LLM architectures for text + voice workflows
• Build GenAI-based workflows and integrate models into production systems.
• Implement RAG pipelines and agent-based systems for complex automation.

Fintech & Banking AI

• Work on AI-driven features related to banking, financial risk, compliance automation, fraud patterns, and customer intelligence.
• Understand fintech data structures and constraints while designing AI models.

Engineering, Deployment & Collaboration

• Deploy models on cloud or on-prem (AWS / Azure / GCP / internal infra).
• Build robust APIs and services for voice and ML-based functionalities.
• Collaborate with data engineers, backend developers, and business teams to deliver end-to-end AI solutions.
• Document systems and contribute to internal knowledge bases and R&D.

Security & Compliance

• Follow fundamental best practices for AI security, access control, and safe data handling.
• Awareness of financial compliance standards (plus, not mandatory).
• Follow internal guidelines on PII, audio data, and model privacy.

Primary Skills (Must-Have)

Core AI

• Machine Learning fundamentals
• Deep Learning architectures
• NLP pipelines and transformers
• LLM usage and integration
• GenAI development
• Voice AI (STT, TTS, VAD, real-time pipelines)
• Audio processing fundamentals
• Model building, tuning, and retraining
• RAG systems
• AI Agents (orchestration, multi-step reasoning)

Voice Engineering

• End-to-end voice application development
• Voice calling & telephony integration (framework-agnostic)
• Realtime STT ↔ LLM ↔ TTS interactive flows
• Voice chat system development
• Voice-to-AI model integration for automation

Fintech/Banking Awareness

• High-level understanding of fintech and banking AI use cases
• Data patterns in core banking analytics (advantageous)

Programming & Engineering

• Python (strong competency)
• Cloud deployment understanding (AWS/Azure/GCP)
• API development
• Data processing & pipeline creation

Secondary Skills (Good to Have)

• MLOps & CI/CD for ML systems
• Vector databases
• Prompt engineering
• Model monitoring & evaluation frameworks
• Microservices experience
• Basic UI integration understanding for voice/chat
• Research reading & benchmarking ability

Qualifications

• 2–3 years of practical experience in AI/ML/DL engineering.
• Bachelor’s/Master’s degree in CS, AI, Data Science, or related fields.
• Proven hands-on experience building ML/DL/voice pipelines.
• Experience in fintech or data-intensive domains preferred.

Soft Skills

• Clear communication and requirement understanding
• Curiosity and research mindset
• Self-driven problem solving
• Ability to collaborate cross-functionally
• Strong ownership and delivery discipline
• Ability to explain complex AI concepts simply

MLSecured(https://www.mlsecured.com/) an AI GRC (Governance, Risk, and Compliance) is Hiring! a Backend Software Engineer 🚀

Are you a passionate Backend Software Engineer with experience in Machine Learning and Open Source projects? Do you have a strong foundation in Python and Object-Oriented Programming (OOP) concepts? Join us at MLSecured.com and be part of our mission to solve AI Security & Compliance challenges! 🔐🤖

What We’re Looking For:

👨‍💻 1-2 years of professional experience in Backend Development and Open Source projects contribution

🐍 Proficiency in Python and OOP concepts

🤝 Experience with Machine Learning (NLP, GenAI)

🤝 Experience with CI/CD and cloud infra is a plus

💡 A passion for solving complex AI Security & Compliance problems

Why Join Us?

At MLSecured.com, you'll work with a talented team dedicated to pioneering AI security solutions. Be a part of our journey to make AI systems secure and compliant for everyone. 🌟

Perks of Joining a Fast-Paced Startup:

🚀 Rapid career growth and learning opportunities

🌍 Work on cutting-edge AI technologies and innovative projects

🤝 Collaborative and dynamic work environment

🎉 Flexible working hours and full remote work options

📈 Significant impact on the company's direction and success

• Back-end software development
• Software engineering and designing data models and write effective APIs
• Working together with engineers and product teams
• Understanding business use cases and requirements for different internal teams
• Maintenance of existing projects and New feature development
• Consume and integrate classifier/ ML snippets from Data science team

What we are looking for:

• 4+ years of industry experience with the Python and Django framework.
• Degree in Computer Science or related field
• Good analytical skills with strong fundamentals of data structures and algorithms
• Experience building backend services with hands-on experience through all stages of Agile software development life cycle.
• Ability to write optimized codes,debug programs, and integrate applications with third party tools by developing various APIs
• Experience with Databases (Relational and Non-Relational). Ex: Cassandra, MongoDB, Postgresql
• Experience with writing REST-APIs.
• Prototyping initial collection and leveraging existing tools and/or creating new tools
• Experience working different types of datasets (e.g. unstructured, semi-structured, with missing information)
• Ability to think critically and creatively in a dynamic environment, while picking up new tools and domain knowledge along the way
• A positive attitude, and a growth mindset

Bonus:

• Experience with relevant Python libraries such as Sklearn, NLTK, tensorflow, HuggingFace Transformers
• Hands on experience in Machine learning implementations
• Experience with Cloud infrastructure (e.g. AWS) and relevant microservices
• Good with Humor and Team player

• Writing efficient, reusable, testable, and scalable code
• Understanding, analyzing, and implementing – Business needs, feature modification requests, conversion into software components
• Integration of user-oriented elements into different applications, data storage solutions
• Developing – Backend components to enhance performance and receptiveness, server-side logic, and platform, statistical learning models, highly responsive web applications
• Designing and implementing – High availability and low latency applications, data protection and security features
• Performance tuning and automation of application
• Working with Python libraries like Pandas, NumPy, etc.
• Creating predictive models for AI and ML-based features
• Keeping abreast with the latest technology and trends
• Fine-tune and develop AI/ML-based algorithms based on results

Good proficiency in,

• Python frameworks like Django, etc.
• Web frameworks and RESTful APIs
• Core Python fundamentals and programming
• Code packaging, release, and deployment
• Database knowledge
• Circles, conditional and control statements
• Object-relational mapping
• Code versioning tools like Git, Bitbucket

Fundamental understanding of,

• Front-end technologies like JS, CSS3 and HTML5
• AI, ML, Deep Learning, Version Control, Neural networking
• Data visualization, statistics, data analytics
• Design principles that are executable for a scalable app
• Creating predictive models
• Libraries like Tensorflow, Scikit-learn, etc
• Multi-process architecture
• Basic knowledge about Object Relational Mapper libraries
• Ability to integrate databases and various data sources into a unified system
• Basic knowledge about Object Relational Mapper libraries
• Ability to integrate databases and various data sources into a unified system