1460 Machine Learning Specialists jobs in Bengaluru

Position :
AI/ML Engineer.

Location :
Bangalore.

Industry :
IT Software.

Experience Required :
3-5 Years.

WFO 5 Days

• The focus is on advanced machine learning, with significant depth in deep learning, large language models, and recommender systems.
• Youll be involved in validation, defect management, and the overall software development life cycle.
• The role requires extensive hands-on experience with Ubuntu/Yocto Linux, as well as popular open-source ML frameworks like PyTorch, TensorFlow, and ONNX Runtime.
• Exposure to profiling ML workloads, end-to-end AI/ML compute stack validation (including HIP, CUDA, OpenCL, OpenVINO, ONNX Runtime, TensorFlow/PyTorch integration), and end-to-end AI pipeline assessment from model conversion to inference and kernel execution.
• Proficiency in Python programming, strong problem-solving skills, and a mindset open to innovative approaches are vital.
• Youll work using global production software quality assurance methodologies, taking strong ownership of deliverables, and collaborating with teams globally.

)

Experience

• 5+ years of professional experience in Machine Learning Engineering, Software Engineering with a strong ML focus, or a similar Programming Skills :
• Expert-level proficiency in Python, including experience with writing production-grade, clean, efficient, and well-documented code.
• Experience with other languages (e.g., Java, Go, C++) is a Software Engineering Fundamentals :
• Deep understanding of software design patterns, data structures, algorithms, object-oriented programming, and distributed Learning Expertise :
• Solid theoretical and practical understanding of various machine learning algorithms
• Proficiency with ML frameworks such as PyTorch, Scikit-learn.
• Experience with feature engineering, model evaluation metrics, and hyperparameter Handling :
• Experience with SQL and NoSQL databases, data warehousing concepts, and processing large :
• Excellent analytical and problem-solving skills, with a pragmatic approach to delivering :
• Strong verbal and written communication skills, with the ability to explain complex technical concepts to both technical and non-technical audiences.

)

Role**: Engineer

Required Technical Skill Set**Artificial Intelligence/ Machine Learning

Experience: 5 to 10 Years

Location: Hyd, Noida, Chennai, Mumbai

Desired Competencies (Technical/Behavioral Competency)

Must-Have**

AI/ML, Azure ML Studio, AI/ML On Databricks, Python & CICD Devops.

Supervised and unsupervised ML and Predictive Analytics using Python

• Feature generation through data exploration and SME requirements

• Relational database querying

• Applying computational algorithms and statistical methods to structured and unstructured data

• Communicating results through data visualizations

Programming Languages: Python, PySpark

• Big Data Technologies: Spark with PySpark

• Cloud Technologies: Azure (ADF, Databricks, Storage Account Usage, WebApp, Key vault, SQL Server, function app, logic app, Synapse, Azure Machine Learning, Azure DevOps)

• RBAC Maintenance for Azure roles.

• Github branching and managing

• Terraform scripting for Azure IAA

• Optional: GCP (Big Query, DataProc, Cloud Storage

Good-to-Have

Responsibility of / Expectations from the Role

Designing, developing, and deploying AI solutions on the Azure platform

Visiting Faculty for the MBA Technology Management Program

Position Title:

Visiting Faculty

Course:

Artificial Intelligence and Machine Learning, MBA

Location:

Yelahanka, Bangalore, Karnataka

Mode:

On Campus, no online classes

Duration:

One Term of a Trimester (extendable based on academic needs and performance)

20th October 2025 to 31st December 2025

Course Overview

The course in Artificial Intelligence and Machine Learning aims to provide management students with a comprehensive understanding of modern AI and ML methods and their business applications. The course combines theoretical underpinnings with hands-on learning through programming, case studies, and applied projects.

Key focus areas include:

• Fundamentals of AI and ML algorithms
• Supervised and unsupervised learning techniques
• Deep learning and neural networks
• Business problem-solving using AI/ML
• Model evaluation, deployment, and ethical considerations

Key Responsibilities

• Design and deliver lectures, tutorials, and hands-on sessions on AI/ML concepts and applications
• Integrate business and management context into technical topics to suit MBA and postgraduate students
• Develop case studies, datasets, and simulation-based exercises
• Mentor students on AI/ML projects and practical applications
• Collaborate with TAPMI faculty on course design, assessment, and AACSB/AoL requirements
• Contribute to guest lectures, workshops, and research/consulting initiatives related to data-driven decision-making

Qualifications

Essential:

• Master’s degree or Ph.D. in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Statistics, or a closely related field
• Demonstrated expertise in AI/ML, with teaching or corporate training experience
• Proficiency in Python, R, or equivalent programming environments for machine learning

Desirable:

• Industry or research experience in applying AI/ML in business or management contexts
• Strong publication or consulting record in applied AI/ML domains
• Familiarity with deep learning frameworks such as TensorFlow, Keras, or PyTorch

Skills and Competencies

• Ability to simplify complex technical concepts for management students
• Strong communication and classroom engagement skills
• Ability to bridge theory with real-world applications
• Collaborative mindset and commitment to academic excellence

Remuneration

Compensation will be commensurate with qualifications, experience, and profile , and in line with TAPMI’s norms for visiting faculty.

Application Process

Interested candidates may send their applications to Prof. Deepak A S ( ), Analytics Area Chair, with the subject line: “Application – Visiting Faculty (Artificial Intelligence and Machine Learning)”

The application should include:

• Detailed CV (with academic, teaching, and industry experience)
• List of two professional references

Job Description: Machine Learning & Generative AI Engineer

• Role:
  Machine Learning & Generative AI Engineer
• Job Location:
  Bangalore (Hybrid – 2-3 days from office)
• Experience:
  3-7 years

We value diverse perspectives and encourage applications from women in technology

About the Role

We are seeking a highly skilled
Machine Learning & Generative AI Engineer
to design, build, and deploy advanced ML and GenAI solutions. This role provides the opportunity to work on cutting-edge AI technologies such as
LLM fine-tuning, Transformer architectures, Retrieval-Augmented Generation (RAG)
, and enterprise-scale ML systems. The ideal candidate will combine strong technical expertise with innovative thinking to deliver impactful AI solutions aligned with business needs.

Required Skills & Qualifications

·   3–7 years of experience in
Machine Learning, Deep Learning, and AI model development

·   Strong proficiency in Python
and ML frameworks:
PyTorch, TensorFlow, Scikit-Learn, MLflow

·   Expertise in Transformer architectures
(BERT, GPT, T5, LLaMA, Falcon, etc.) and
attention mechanisms

·   Hands-on experience with Generative AI
: LLM fine-tuning (LoRA, QLoRA, PEFT, full model tuning), instruction tuning, and
prompt optimization

·   Experience with RAG pipelines
– embeddings, vector databases (FAISS, Pinecone, Weaviate, Chroma), and retrieval workflows

·   Strong foundation in
statistics, probability, and optimization techniques

·   Proficiency with cloud ML platforms
(Azure ML / Azure OpenAI, AWS SageMaker / Bedrock, GCP Vertex AI)

·   Familiarity with
Big Data & Data Engineering
: Spark, Hadoop, Databricks, SQL/NoSQL databases

·   Hands-on experience with
CI/CD, MLOps, and automation pipelines
(Airflow, Kubeflow, MLflow)

·   Experience with
Docker, Kubernetes
for scalable ML/LLM deployment

Preferred Qualifications

·   Experience in
NLP & Computer Vision
(Transformers, BERT/GPT models, YOLO, OpenCV)

·   Knowledge of
vector search & embeddings
for enterprise-scale GenAI solutions

·   Exposure to
multimodal AI
(text + image/video/audio) and
Edge AI / federated learning

·   Familiarity with RLHF (Reinforcement Learning with Human Feedback)
for LLMs

·   Understanding of
real-time ML applications
and
low-latency model serving

Key Responsibilities

·   Design, build, and deploy
end-to-end ML pipelines
including data preprocessing, feature engineering, model training, and deployment

·   Develop and optimize
LLM-based solutions
leveraging Transformer architectures for enterprise applications

·   Implement
RAG pipelines
using embeddings and vector databases to integrate domain-specific knowledge into LLMs

·   Fine-tune LLMs on
custom datasets
(text corpora, Q&A, conversational data, structured-to-text) for specialized tasks

·   Ensure
scalable deployment
of ML & LLM models on cloud environments with monitoring, versioning, and performance optimization

·   Collaborate with
data scientists, domain experts, and software engineers
to deliver AI-driven business impact

What We're Looking For

Beyond technical skills, the ideal candidate should excel in:

·   Real-world AI application & deployment

·   Prompt engineering & model evaluation

·   Fine-tuning & customization of LLMs

·   Understanding of LLM internals & ecosystem tools

·   Creativity, problem-solving & innovation

·   Business alignment, security, and ethical AI practices

Integers.Ai is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

We're AtkinsRéalis, a world class Engineering Services and Nuclear organization. We connect people, data and technology to transform the world's infrastructure and energy systems. Together, with our industry partners and clients, and our global team of consultants, designers, engineers and project managers, we can change the world. Created by the integration of long-standing organizations dating back to 1911, we are a world-leading professional services company dedicated to engineering a better future for our planet and its people. We deploy global capabilities locally to our clients and deliver unique end-to-end services across the whole life cycle of an asset including consulting, advisory & environmental services, intelligent networks & cybersecurity, design & engineering, procurement, project & construction management, operations & maintenance, decommissioning and capital. The breadth and depth of our capabilities are delivered to clients in key strategic sectors.

News and information are available at or follow us on LinkedIn.

Our teams take great pride in delivering some of the world's most prestigious projects. This success is driven by our talented people, whose diverse perspectives, expertise, and knowledge set us apart. Join us and you'll be part of our genuinely collaborative environment, where everyone is supported to make the most of their talents and expertise.

When it comes to work-life balance, AtkinsRéalis is a great place to be. So, let's discuss how our flexible and remote working policies can support your priorities. We're passionate about are work while valuing each other equally. So, ask us about some of our recent pledges for Women's Equality and being a 'Disability Confident' and 'Inclusive Employer'.

Key Responsibilities

• Data Collection & Pipeline Development:

• Collect and curate a large-scale dataset of urban, architectural, and interior design images, including floor plans, room scenes, building exteriors, and construction details.

• Develop robust data pipelines for preprocessing (resizing, labeling styles or room types, tagging materials, etc.) to ensure high-quality, domain-relevant training data.

• Maintain data versioning and augmentation pipelines to boost model robustness and ensure traceability.

• Model Training & Optimization:

• Lead the implementation of the end-to-end training pipeline, including GPU setup (cloud or on-premise), training workflows, and runtime optimization.

• Train and fine-tune generative models and computer vision systems, monitoring performance and adjusting parameters for maximum quality and efficiency.

• Deployment & MLOps:

• Deploy trained models into production environments (cloud APIs or integrations within design software).

• Establish MLOps practices for continuous integration of model updates, automated retraining, model version control, and CI/CD for ML services.

• Optimize model inference (quantization, model compression) to deliver low-latency, high-reliability performance to end-users.

• Evaluation & Quality Assurance:

• Work with the AI Research Scientist and Product/Design Lead to test model outputs and ensure alignment with architectural design standards.

• Implement evaluation metrics that reflect domain needs — e.g., accuracy of architectural details, style coherence, or alignment with user-specified parameters.

• Required Qualifications:

• Master's degree in Computer Science, Data Science, or a related field (or strong practical experience equivalent).

• Proficiency in Python (and possibly C++ for performance-critical components). Experience in building robust data and ML pipelines using frameworks such as Pandas, NumPy, and cloud data storage for handling millions of images.
• ML Expertise: Hands-on experience training deep learning models for images, with knowledge of MLOps tools and best practices – e.g., MLflow or Kubeflow for experiment tracking, Docker for containerization, and continuous deployment.
• Strong understanding of image augmentation, CNNs, and evaluation metrics (FID, precision/recall) for generative models. Familiarity with generative AI frameworks such as Stable Diffusion, GAN libraries, or vision transformers.

• Domain Familiarity: Understanding of urban, architecture, and interior design datasets and workflows is a significant plus.

• Relevant Experience/Background:

• Full Lifecycle ML Projects: Prior experience taking a machine learning project from problem definition and data preparation to model training, deployment, and monitoring in production.

• Large-Scale Data Handling: Experience managing datasets of hundreds of thousands or more images where data volume and pipeline reliability were critical (e.g., imaging company, autonomous driving dataset, or large content platform).
• AEC/Design Tech: Experience specifically in the architecture, engineering, construction (AEC) or design technology field is highly valuable, understanding CAD/BIM data or architectural imagery workflows helps ensure better model performance.
• Software/DevOps: History of building reliable web services or tools (not just ML prototypes), indicating the ability to create a stable, production-grade AI platform.

What We Can Offer You

• Varied, interesting and meaningful work.
• A hybrid working environment with flexibility and great opportunities.
• Opportunities for training and, as the team grows, career progression or sideways moves.
• An opportunity to work within a large global multi-disciplinary consultancy on a mission to change the ways we approach business as usual.

Why work for AtkinsRéalis?
We at AtkinsRéalis are committed to developing its people both personally and professionally. Our colleagues have the advantage of access to a high ranging training portfolio and development activities designed to help make the best of individual's abilities and talents. We also actively support staff in achieving corporate membership of relevant institutions.

Meeting Your Needs
To help you get the most out of life in and outside of work, we offer employees 'Total Reward'.

Making sure you're supported is important to us. So, if you identify as having a disability, tell us ahead of your interview, and we'll discuss any adjustments you might need.

Additional Information
We are an equal opportunity, drug-free employer committed to promoting a diverse and inclusive community - a place where we can all be ourselves, thrive and develop. To help embed inclusion for all, from day one, we offer a range of family friendly, inclusive employment policies, flexible working arrangements and employee networks to support staff from different backgrounds. As an Equal Opportunities Employer, we value applications from all backgrounds, cultures and ability.

We care about your privacy and are committed to protecting your privacy. Please consult our Privacy Notice on our Careers site to know more about how we collect, use and transfer your Personal Data.

Link: Equality, diversity & inclusion | Atkins India )

1. Job Title: Machine Learning (ML) Architect

Summary:The Machine Learning Architect designs and oversees AI/ML architecture for scalable enterprise solutions. This role sets technical direction, drives ML operations (MLOps), ensures high model performance, security, compliance, and bridges data, engineering, and business objectives.

Key Responsibilities:

• Architect and maintain ML pipelines spanning data preparation, model training, deployment, monitoring, and retraining.
• Define standards/best practices for MLOps, feature management, model versioning, CI/CD, and model registry.
• Collaborate with DevOps, Security, Compliance and Data Governance teams on infrastructure and policies.
• Evaluate, select, and integrate appropriate frameworks and platforms (PyTorch, TensorFlow, AWS Sagemaker, Vertex AI, Kubeflow, etc.).
• Optimize computational resource utilization and cost for cloud/hybrid environments.
• Lead technical design reviews, root cause analyses, and system troubleshooting.
• Document architecture and mentor teams in scalable ML solution design.

Required Skills:

• Deep knowledge of ML algorithms, statistical modeling, data engineering, and distributed systems.
• Strong programming (Python, Scala, Java) and hands-on MLOps exposure.
• Cloud expertise (AWS, Azure, GCP), especially ML-native services.
• Proficiency in containerization/orchestration (Docker, Kubernetes).
• Familiarity with CI/CD pipelines, GitOps, and Infrastructure as Code.
• Excellent communication, system documentation, and leadership skills.

Preferred Qualifications:

• Experience with Explainable AI, responsible AI, and ML governance.
• Prior experience leading large-scale deployments of ML solutions.

Tools & Technologies:Python, PyTorch, TensorFlow, MLFlow, Airflow, AWS, GCP, AzureML, Docker, Kubernetes, Apache Spark.

Experience:8+ years in ML/Data Science/Software Engineering, 3+ years architecture leadership.

Education:Bachelor's/Master's in Computer Science, Data Science, or similar technical field.

Job Type: Full-time

Pay: ₹4,000, ₹6,000,000.00 per year

Work Location: In person