Calix

Staff Software Engineer – AI/ML

Calix

full-time

Posted on:

Location Type: Hybrid

Location: Bangalore • 🇮🇳 India

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Job Level

Lead

Tech Stack

AWSAzureCloudDockerGoGoogle Cloud PlatformJavaKubernetesNumpyPandasPythonPyTorchScikit-LearnSQLTensorflow

About the role

  • Design and Build ML Models: Develop and implement advanced machine learning models (including deep learning architectures) for generative tasks, such as text generation, image synthesis, and other creative AI applications.
  • Optimize Generative AI Models: Enhance the performance of models like GPT, V AEs, GANs, and Transformer architectures for content generation, making them faster, more efficient, and scalable.
  • Data Preparation and Management: Preprocess large datasets, handle data augmentation, and create synthetic data to train generative models, ensuring high-quality inputs for model training.
  • Model Training and Fine-tuning: Train large-scale generative models and fine-tune pre-trained models (e.g., GPT, BERT, DALL-E) for specific use cases, using techniques like transfer learning, prompt engineering, and reinforcement learning.
  • Performance Evaluation: Evaluate models’ performance using various metrics (accuracy, perplexity, FID, BLEU, etc.), and iterate on the model design to achieve better outcomes.
  • Collaboration with Research and Engineering Teams: Collaborate with cross-functional teams, including AI researchers, data scientists, and software developers, to integrate ML models into production systems.
  • Experimentation and Prototyping: Conduct research experiments and build prototypes to test new algorithms, architectures, and generative techniques, translating research breakthroughs into real-world applications.
  • Deployment and Scaling: Deploy generative models into production environments, ensuring scalability, reliability, and robustness of AI solutions in real-world applications.
  • Stay Up-to-Date with Trends: Continuously explore the latest trends and advancements in generative AI, machine learning, and deep learning to keep our systems at the cutting edge of innovation.

Requirements

  • Bachelor’s, Master’s, or Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, Data Science, or a related field.
  • 8+ years of overall software engineering in production.
  • 3-5+ years of focus on Machine Learning.
  • Proven experience with generative AI models such as GPT, V AEs, GANs, or Transformer architectures.
  • Strong hands-on experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX.
  • Strong coding experience in Python, Java, Go, C/C++, R.
  • Expertise in Python and libraries such as NumPy, Pandas, and Scikit-learn.
  • Experience with Natural Language Processing (NLP), image generation, or multimodal models.
  • Familiarity with training and fine-tuning large-scale models (e.g., GPT, BERT, DALL-E).
  • Knowledge of cloud platforms (AWS, GCP, Azure) and ML ops pipelines (e.g., Docker, Kubernetes) for deploying machine learning models.
  • Strong background in data manipulation, data engineering, and working with large datasets.
  • Good data skills - SQL, Pandas, exposure to various SQL and non-SQL databases.
  • Solid development experience with dev cycle on Testing and CICD.
  • Strong problem-solving abilities and attention to detail.
  • Excellent collaboration and communication skills to work effectively within a multidisciplinary team.
  • Proactive approach to learning and exploring new AI technologies.
Benefits
  • Flexible hybrid work model - work from Bangalore office for 20 days in a quarter

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard skills
machine learningdeep learninggenerative AIGPTV AEsGANsTransformer architecturesPythonTensorFlowPyTorch
Soft skills
problem-solvingattention to detailcollaborationcommunicationproactive learning