SEO

Gieom is a software product company working with Banks and Financial institutions across the globe, implementing software solutions in the areas of Operational Risk & Resilience, GRC and SOP Digitization.

Currently we are looking for candidates for Business Analyst role. The candidate is expected to possess knowledge is any of the areas as mentioned above with experience of 1-3 years in similar area. The candidate will be interacting with Risk teams of global banks to understand their requirements of enterprise risk management and help the bank / financial entity to implement their risk solution. 

Responsibility

• Work in the areas of Governance, Risk & Compliance (GRC) and Process Management
• Be part of project teams implementing solutions for global banks and financial institutions
• Liaise with client stakeholders to gather requirements, map processes, document needs, configure systems, and support project delivery
• Quickly learn products and deliver presentations on requirements and solutions
• Collaborate with Pre-Sales, Product teams, and clients for POCs and successful implementations
• Work closely with Product teams to understand new features and use cases
• Conduct independent industry and competitor research and contribute to marketing content such as case studies and blogs

Ideal Candidate

• Fresher or up to 3 years of relevant experience
• Excellent written and verbal communication skills (mandatory for global client interaction)
• Willing to undertake long-duration local and international travel
• Risk certifications or finance/operations qualifications preferred
• Strong fundamentals in finance and operations (mandatory)
• Qualification MBA/CA
• Ready to join immediate

• 7+ years in Data, AI, or Advanced Analytics • 3+ years hands-on experience with GenAI / LLM ecosystems • Strong understanding of: ➢ LLM architectures ➢ Prompt engineering ➢ RAG pipelines ➢ AI evaluation frameworks ➢ MLOps & deployment • Experience in regulated industries (Pharma preferred) • Proven consulting or client-facing experience .

Roles and responsibilities: • Combines technical depth + business breadth • Thinks in scalable frameworks, not one-off solutions Driving Innovation, Empowering Insights  • Comfortable speaking to both engineers and VP/SVP/CXOs • Revenue-aware, not just technically strong • High ownership mindset (“runs toward complexity”) • AI-native thinker - uses AI daily to improve productivity 

Roles and Responsibilities:-

1. Developing, generating, and growing new digital marketing business

2. Creating innovative online marketing sales plans

3. Exhibiting expertise in digital marketing solutions

4. Selling services like SEO, SEM, PPC, social media, online reputation management, etc. (for the

US and Canada locations)

5. Maintaining accurate and up-to-date pipeline and forecasts

Desired Candidate Profile:-

1. The position demands an entrepreneurial-minded individual with high energy and a strong motivation to sell (we like increasing numbers)

2. A strong candidate will have excellent sales and closing skills

3. Strong organizational skills and ability to handle multiple tasks and priorities

4. Demonstrated time management skills

5. Knowledge of digital marketing/SEO services will be a plus

6. Excellent communication skills

Working Days: Monday to Friday

Shift: Night Shift(7:00PM to 4:00AM)

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

Skills: Machine Learning,Deep Learning,Artificial Intelligence,python.

Location:Chennai


Domain knowledge: Data cleaning, modelling, analytics, statistics, machine learning, AI

Requirements:

·         To be part of Digital Manufacturing and Industrie 4.0 projects across Saint Gobain group of companies

·         Design and develop AI//ML models to be deployed across SG factories

·         Knowledge on Hadoop, Apache Spark, MapReduce, Scala, Python programming, SQL and NoSQL databases is required

·         Should be strong in statistics, data analysis, data modelling, machine learning techniques and Neural Networks

·         Prior experience in developing AI and ML models is required

·         Experience with data from the Manufacturing Industry would be a plus

Roles and Responsibilities:

·         Develop AI and ML models for the Manufacturing Industry with a focus on Energy, Asset Performance Optimization and Logistics

·         Multitasking, good communication necessary

·         Entrepreneurial attitude.

Responsibilities:

• Good understanding of programming language
• Concepts of Java, Maven
• Source Control
• Logically Strong in coding practices
• Data structure Understanding.
• Security encryption and decryption
• Data encoding decoding

Requirements:

• Strong core Java development skills.
• Exposure to security tools.
• Experience in working with customers, understanding business requirements
• Good analytical and troubleshooting skills.
• Working knowledge of Jenkins/Maven
• Key requirements: Core Java, CI/CD, Docker, Maven, Jenkins, REST API, Kafka, Redis, cache, elastic cache

Job Responsibilities

• Set-up gameplay mechanics
• Responsible for bringing fun elements to the game
• Work with designers and artists to deliver project on time

Skills Required

• Expertise in Javascript/Typescript
• Experience building games in any WebGL engine like Cocos, Phaser, Playcanvas, Babylon
• Experience with optimisations and building optimised game projects
• Excellent problem-solving ability
• Passionate about playing and developing best-in-class video game experiences
• Ability to pick up new game engines and read other people's code.
• Transparent and to-the-point communication skills.

Perks

• Best salary in the segment
• Amazing workplace environment
• Insurance and PF
• Remote work option

Job Description: 

An Azure Data Engineer is responsible for designing, implementing, and maintaining pipelines and ETL/ ELT flow solutions on the Azure cloud platform. This role requires a strong understanding of migration database technologies and the ability to deploy and manage database solutions in the Azure cloud environment.

Key Skills:

·      Min. 3+ years of Experience with data modeling, data warehousing, and building ETL pipelines.

·      Must have a firm knowledge of SQL, NoSQL, SSIS SSRS, and ETL/ELT Concepts.

·      Should have hands-on experience in Databricks, ADF (Azure Data Factory), ADLS, Cosmos DB.

·      Excel in the design, creation, and management of very large datasets

·      Detailed knowledge of cloud-based data warehouses, architecture, infrastructure components, ETL, and reporting analytics tools and environments.

·      Skilled with writing, tuning, and troubleshooting SQL queries

·      Experience with Big Data technologies such as Data storage, Data mining, Data analytics, and Data visualization.

·      Should be familiar with programming and should be able to write and debug the code in any of the programming languages like Node, Python, C#, .Net, Java.

Technical Expertise and Familiarity:

• Cloud Technologies: Azure (ADF, ADB, Logic Apps, Azure SQL database, Azure Key Vaults, ADLS, Synapse)
• Database: CosmosDB, Document DB  
• IDEs: Visual Studio, VS Code, MS SQL Server
• Data Modelling,ELT, ETL Methodology