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Artificial Intelligence Machine Learning Engineer

Hyderabad Pune
Python TensorFlow PyTorch Docker Kubernetes AWS GCP Azure SQL Machine Learning Deep Learning Generative AI Hugging Face Transformers MLflow GANs VAEs Neural Networks GPT BERT T5
Description

AI ML Engineer - 42584

Location: Pune

Department: Engineer

Experience: 2-4

Role: AI ML Engineer - 42584
Experience: 2+ years
No. of positions: 3
Location: Hyderabad / Pune

Fission Labs, Headquartered in Sunnyvale, with offices in Dallas & Hyderabad, Fission Labs is a leading software development company, specializing in crafting flexible, agile, and scalable solutions that propel businesses forward. With a comprehensive range of services, including product development, cloud engineering, big data analytics, QA, DevOps consulting, and AI/ML solutions, we empower clients to achieve sustainable digital transformation that aligns seamlessly with their business goals.

What are we looking for:
Results-driven AI/ML Engineer with expertise in designing, training, and deploying scalable machine learning and deep learning models. Skilled in Python, TensorFlow, and cloud-based AI solutions, with strong experience in data preprocessing, model optimization, and MLOps integration and Generative AI. Adept at translating complex business challenges into AI-driven insights and automation.

Responsibilities
  • Design, develop, and deploy advanced AI models with a focus on generative AI, including transformer architectures (e.g., GPT, BERT, T5) and other deep learning models used for text, image, or multimodal generation
  • Work with extensive and complex data sets, performing tasks such as cleaning, preprocessing, and transforming data to meet quality and relevance standards for generative model training.
  • Collaborate with cross-functional teams (e.g., product, engineering, data science) to identify project objectives and create solutions using generative AI tailored to business needs.
  • Implement, fine-tune, and scale generative AI models in production environments, ensuring robust model performance and efficient resource utilization.
  • Develop pipelines and frameworks for efficient data ingestion, model training, evaluation, and deployment, including A/B testing and monitoring of generative models in production.
  • Stay informed about the latest advancements in generative AI research, techniques, and tools, applying new findings to improve model performance, usability, and scalability.
  • Document and communicate technical specifications, algorithms, and project outcomes to technical and non-technical stakeholders, with an emphasis on explain ability and responsible AI practices

Qualifications Required
Educational Background:
  • Bachelor’s or master’s degree in computer science,
  • Data Science, AI/ML, or a related field. Relevant Ph.D. or research experience in generative AI is a plus.

Experience:
  • 2-4 years of experience in machine learning, with 2+ years in designing and implementing generative AI models or working specifically with transformer-based models

Technical Expertise:
  • Proficiency in Python, along with experience in libraries and frameworks central to generative AI, such as Hugging Face Transformers, PyTorch, and TensorFlow.
  • Strong understanding of transformer architectures, language models, and generative modeling techniques (e.g., GANs, VAEs, autoregressive models).
  • Expertise in data processing techniques for training large language models, including handling unstructured data, tokenization, and feature extraction.
  • Familiarity with ML Ops practices and tools (e.g., Docker, Kubernetes, ML flow) for deploying and managing large-scale models in production.
  • Experience with cloud platforms (AWS, GCP, Azure) and GPU/TPU resources for training and fine-tuning large models

Core Skills:
  • Machine Learning: Strong foundation in machine learning algorithms, deep learning, generative AI techniques.
  • Programming :Proficient in Python, with knowledge of SQL for data handling and retrieval.
  • Data Engineering: Experience with data preprocessing, feature engineering, and data transformation specific to large and complex datasets
  • Model Evaluation: Knowledge of model evaluation metrics and techniques for generative models, especially for text generation, image synthesis, or multimodal AI

Soft Skills:
  • Strong analytical and problem-solving skills with a high level of attention to detail.
  • Excellent communication skills, with the ability to explain complex generative AI concepts to both technical and non-technical audiences.
  • Collaborative mindset with the capability to work effectively in cross-functional teams.

 Skills and Experience Required
  • Generative AI: Transformer Models, GANs, VAEs, Text Generation, Image Generation
  • Machine Learning: Algorithms, Deep Learning, Neural Networks
  • Programming: Python, SQL; familiarity with libraries such as Hugging Face Transformers, PyTorch, TensorFlow
  • MLOps: Docker, Kubernetes, MLflow, Cloud Platforms (AWS, GCP, Azure)
  • Data Engineering: Data Preprocessing, Feature Engineering, Data Cleaning
 
You would enjoy
  • Opportunity to work on impactful technical challenges with global reach.
  • Vast opportunities for self-development, including online university access and knowledge sharing opportunities.
  • Sponsored Tech Talks & Hackathons to foster innovation and learning.
  • Generous benefits packages including health insurance, retirement benefits, flexible work hours, and more.
  • Supportive work environment with forums to explore passions beyond work.
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