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We are looking for a
Machine Learning & Generative AI Engineer
to design, build, and deploy advanced ML and GenAI solutions. This role offers an exciting opportunity to work on
cutting-edge AI systems
, including
LLM fine-tuning, Transformer architectures, and RAG pipelines
, while also driving traditional ML model development for decision-making and automation.

Key Skills Required

• 3–7 years in Machine Learning, Deep Learning, and AI model development
• Strong proficiency in Python, PyTorch, TensorFlow, Scikit-Learn, MLflow
• Expertise in Transformer architectures (BERT, GPT, T5, LLaMA, Falcon, etc.) and attention mechanisms
• Experience with Generative AI: LLM fine-tuning (LoRA, QLoRA, PEFT, full model tuning), instruction tuning, and prompt optimization
• Hands-on with RAG (Retrieval-Augmented Generation) – embeddings, vector databases (FAISS, Pinecone, Weaviate, Chroma), and retrieval workflows
• Strong foundation in statistics, probability, and optimization techniques
• Experience with cloud ML platforms: Azure ML / Azure OpenAI, AWS SageMaker / Bedrock, or GCP Vertex AI
• Familiarity with Big Data & Data Engineering: Spark, Hadoop, Databricks, SQL/NoSQL databases
• Proficiency in CI/CD, MLOps, and automation pipelines (Airflow, Kubeflow, MLflow)
• Hands-on with Docker, Kubernetes for scalable ML/LLM deployment

Good to Have

• NLP & Computer Vision: Transformers, BERT/GPT models, YOLO, OpenCV
• Experience with vector search & embeddings for enterprise-scale GenAI solutions
• Exposure to multimodal AI (text + image/video/audio) and Edge AI / federated learning
• Knowledge of RLHF (Reinforcement Learning with Human Feedback) for LLMs
• Familiarity with real-time ML applications and low-latency model serving

Role Responsibilities

• Design, build, and deploy end-to-end ML pipelines – data preprocessing, feature engineering, model training, and deployment
• Develop and optimize LLM-based solutions for enterprise use cases, leveraging Transformer architectures
• 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 domain-specific tasks
• Ensure scalable deployment of ML & LLM models on cloud environments with monitoring, versioning, and performance optimization
• Collaborate with cross-functional teams (data scientists, domain experts, software engineers) to deliver AI-driven business impact

Must have:

- Strong experience in proper model deploying,logging, API development/deployment Verteaxi,GCP, Python, SQL & Deep learning,

- Created, deployed, scheduled and monitored multiple ML based applications (Knowledge of model lifecycle: training validation deployment monitoring)

Essential Skills:

• Proven experience (5+ years) in large scale AIMLDS development and deployment

• Proven work and experience (3+ years) with handling large volumes of data

• Deep knowledge and experimentation with Gen Ai and associated components

• Strong knowledge and experience (5+ years) with of Python and SQL

• Preferred

• Proven Experience (2+ years) with Gen AI and its components like Proprietary LLMs, custom LLM deployments, Vector Search, fine-tuning models

• Proven experience (2+ years) with Search engine development and deployment as hybrid search, re-ranking algorithms, sparse and dense embedding generation and usage

Proven experience with development and deployment of low latency search applications.

Machine Learning Engineer (Contract)

Location: Remote (India)

Experience: 5+ Years

Contract Type: 6 Months

Job Summary:

We're hiring a Machine Learning Engineer to build and deploy intelligent systems for real-world applications. This contract role is perfect for someone passionate about AI/ML and experienced in production-grade model development.

Responsibilities:

• Develop, train, and optimize ML models using Python and modern frameworks
• Collaborate with data scientists and engineers to integrate models into production
• Implement MLOps pipelines and monitor model performance
• Conduct experiments, A/B testing, and continuous model improvement
• Stay updated with the latest in AI/ML research and tools

Requirements:

• 5+ years of experience in machine learning and data science
• Hands-on with TensorFlow, PyTorch, Scikit-learn, and MLflow
• Experience with cloud platforms (GCP preferred) and containerization (Docker/Kubernetes)
• Strong understanding of supervised, unsupervised, and deep learning techniques
• Bachelor's or Master's in Computer Science, AI, or related field

Job Types: Contractual / Temporary, Freelance

Contract length: 6 months

Pay: ₹70, ₹90,000.00 per month

Work Location: Remote

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.

June 10, 2022 Edison I

Expired on: Sep 7, 2022

Experience:
5+yrs

Job Type:
Full Time

Job Location:
Bangalore Chennai Coimbatore Pune

Job Description –

• Should have good understanding on AI concepts and also must have project experience building ML algorithms
• Must have complete understanding on various data storage methods and integration of all formats of data (Structured and unstructured data models)
• Must be able to design and develop components that caters the frontend applications or expose as APIs for consumptions
• Should have good exposure and understanding on AWS/Azure platform.
• Must understand the Agile process and devops implementation and deployment procedures.
• should be having good experience on Data mining and data cleansing activities.
• should have better understanding on open source market products.
• must have good communication and presentation skills

Sorry This job has expired, please share your updated resume for future consideration.

Your Updated Resume
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A machine learning (ML) job involves designing, building, and deploying AI systems that learn from data to make predictions and automate tasks. Key responsibilities include data preprocessing, statistical analysis, developing and training ML models, implementing algorithms, testing and evaluating performance, and collaborating with data scientists and software engineers. The goal is to create efficient, scalable, and self-improving AI solutions for various business applications. Key Responsibilities:

• Data Management:Collect, clean, preprocess, and analyze large datasets to identify patterns and prepare them for model training.
• Model Development:Design, develop, and implement machine learning algorithms and models, including neural networks, for specific tasks like classification, prediction, and forecasting.
• Training and Optimization:Train and retrain models, using test results to evaluate their performance and optimize them for higher accuracy and efficiency.
• System Design:Create and scale data and model pipelines, design and build AI systems, and integrate them into real-world applications.
• Testing & Evaluation:Conduct experiments and tests on AI systems, evaluate model performance, and identify issues or areas for improvement.
• Collaboration:Work with data scientists, data engineers, and business teams to understand requirements, translate them into ML solutions, and ensure models are integrated into workflows.
• Continuous Improvement:Stay updated on the latest advancements in machine learning, explore new techniques, and continuously improve existing models and frameworks.

Essential Skills & Tools:

• Programming:Proficiency in programming languages like Python or R is crucial.
• ML Frameworks:Experience with machine learning frameworks such as TensorFlow or PyTorch is often required.
• Data Science & Statistics:Strong understanding of statistical analysis and data science principles to drive decisions and optimize models.
• Big Data Technologies:Familiarity with big data tools and technologies for handling large datasets.
• Problem-Solving:Ability to analyze complex problems and develop innovative, data-driven solutions.

Job Type: Full-time

Pay: ₹471, ₹1,787,189.77 per year

Work Location: Remote

Responsibilities:

• Design, train, and evaluate machine learning models, optimizing for performance and scalability.
• Develop efficient data pipelines, ensuring high-quality training and inference data.
• Analyze and compare ML algorithms to determine the most effective approaches.
• Explore and visualize data to identify patterns and insights.
• Implement feature engineering, data augmentation, and validation strategies.

Job Types: Full-time, Permanent

Work Location: In person

Role & responsibilities Machine Learning

A machine learning expert should not only be able delve into concepts such as data analytics, big data, artificial intelligence, machine learning and deep learning, etc., Also help other team member in by challenging the thought process and bringing in innovative thinking. Ensuring the execution through collaborative working and problem solving. This role will require areas to be identified for value creation that will benefit from new technology, technique or algorithm deployment. The candidate is expected to possess a strong technical and business competency with knowledge of current industry Machine Learning standards, structures, and best practices, and who is capable of identifying current industry challenges in Telecom Network space, which can be solved using data science.

Machine Learning Specialist qualifications and Experience

Machine Learning:

1. Python (Advance level with complex algorithms)

2. R (Advance level with complex algorithms)

Visualization

1. Monitoring with Prometheus and Grafana

2. Tableau and Click View

Container and Storage:

1. Kubernetes

2. Docker

Working knowledge of Data Management Platforms:

1. NiFi, Kafka, HDFS, Hive

2. PostgreSQL

3. NetApp storage

4. IBM Spectrum Scale storage

5. FreeIPA role based access control (RBAC)

Functional Domain Knowledge:

1. Approx 10-15 years industry experience, preferably in Telecom. Major part of this in implementation of artificial intelligence based technologies to enhance operations and processes.

2. Sound knowledge of Cisco hardware, RF, RAN, Transport, Core and Applications.

3. OR Previous working experience as a Machine Learning/ Data Scientist for more than 10 years

4. Master or greater degree in Data science, computer science, mathematics, or statistics from a nationally or internationally recognized institution.

5. Outstanding problem solving and analytical skills, Attention to detail

6. Excellent project and time management skills

7. It will be good to have an exposure of consulting in the field of data science or having record of publications

8. Fluent communication skills in English are a requirement.

Roles and Responsibilities

1. The ML specialist/consultant will include the development of strategic related outlooks, roadmaps with tangible milestones and deliverables.

2. This role requires the ability to guide and mentor multidisciplinary technology teams, support development of training plans for employees within the field of Artificial Intelligence and Machine Learning.

3. Propose new strategies and develop plans to expand the field of application of Machine learning and artificial intelligence within Telecom Network space.

4. Maintain up to date on new trends and techniques for data science based applications in wireless or wireline network to ensure a resilient plan for value realization

5. Establish and manage collaborations within NSG, CMI and other units as well as external partners to accelerate the achievement of goals and maximize the impact of initiatives.

6. Design and develop machine learning algorithms in Telecom Network space wireless or wireline.

7. Discover, design, and develop analytical methods to support novel approaches of data and information processing in the Telecom Networks

8. Provide technical support for program management and business development activities including proposal writing and customer development

9. Create and monitor research programs for new proposed technologies, all while aligned with new business trends.

10. Present technical and techno-commercial acumen to support different responses to clients /Bids / RFPs.

About The Role  

Location:  Pune, India

Role Overview: 

We are seeking a Senior Machine Learning Software Engineer  to join our team and drive the development of cutting-edge AI/ML solutions . You will play a key role in designing, building, and optimizing  our machine learning infrastructure  while collaborating with Product Managers, Data Scientists, and Engineers  to bring innovative models into production. The ideal candidate should have a strong background in ML operations, software engineering, and automation  to ensure a scalable and robust AI-driven ecosystem.

Key Responsibilities:- Operationalize  leading data and analytics technologies  while following best practices.
- Partner with Product Managers  to understand customer requirements, design prototypes, and deploy solutions to production .
- Design, build, harden, and maintain  the core infrastructure supporting the ML platform and lifecycle .
- Define and contribute to the technology strategy, roadmap, and priorities  for AI/ML initiatives.
- Automate every aspect of the ML infrastructure  to minimize human intervention  and improve efficiency.
- Encourage and implement best practices  in data engineering and software development .
- Write high-quality, production-grade code  that aligns with company standards and contribute to new standardization efforts .
- Implement automated testing  to ensure reliability and correctness of ML models and infrastructure.
- Review and mentor  other engineers to promote high-quality engineering practices.
- Actively participate in technical communities-of-practice  and continuing education programs  to advance personal and organizational growth.
- Facilitate problem diagnosis and resolution  across technical and functional  areas.
Required Skills & Competencies:- 8+ years  of experience in software engineering, machine learning, or data engineering .
- Expertise in designing, coding, and scripting  to develop real-world AI/ML solutions .
- Strong programming skills in Python, Java, or Scala  with hands-on experience in ML frameworks.
- Experience with ML model deployment, MLOps, and automation .
- Proficiency in cloud-based ML solutions.
- Knowledge of data pipeline orchestration tools.
- Strong background in data engineering concepts.
- Experience working with containerization.
- Strong analytical and problem-solving skills with a collaborative mindset .
- Excellent communication and leadership skills  with the ability to mentor and guide  junior engineers.