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Salary
$47k – $121k per year (Estimated)
Location
In office (Bengaluru)
Seniority
Senior
Employment
Full-Time
Overview
Company
Impact
Profile match
Weekday is an Indian recruitment company that sources software engineers through referrals from other engineers rather than through job advertisements or agency databases. Its model pays working engineers to vouch for former colleagues they rate, turning informal knowledge about who is genuinely good into a searchable candidate pool that companies can hire from. Based in Bengaluru and backed by Y Combinator, the platform has layered AI screening and outbound sourcing on top of that referral network, and sells to startups and technology companies hiring in the Indian market.

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: - ( - )

Experience: 5+ yrs

Location: Bangalore

Job Type: Full-time

We are looking for an experienced Senior AI/ML Engineer to design, develop, and deploy intelligent machine learning solutions that solve complex business problems and improve operational efficiency.

The ideal candidate will have strong expertise in machine learning, artificial intelligence, Python, data processing, model development, and production deployment. You will work closely with engineering, product, and business teams to translate requirements into scalable AI/ML solutions and take models from experimentation through production.

Requirements

KEY RESPONSIBILITIES

  • Design, develop, test, and deploy scalable AI/ML models and solutions.
  • Work with large and complex datasets to perform data preparation, transformation, feature engineering, and analysis.
  • Develop and optimise machine learning models based on business and product requirements.
  • Evaluate model performance using appropriate metrics, validation techniques, and experimentation frameworks.
  • Build production-ready ML pipelines and integrate models into scalable applications and services.
  • Develop APIs and backend services to support AI/ML capabilities.
  • Work with modern Generative AI and LLM technologies where applicable.
  • Develop solutions involving NLP, predictive modelling, classification, recommendation, or other relevant ML techniques.
  • Experiment with different algorithms, architectures, prompts, models, and approaches to improve performance.
  • Collaborate with software engineers, product managers, data professionals, and other stakeholders to deliver end-to-end AI solutions.
  • Monitor model performance, data quality, system reliability, and production behaviour.
  • Troubleshoot model, data, and production issues and implement sustainable improvements.
  • Optimise models and ML systems for accuracy, scalability, latency, and cost.
  • Contribute to MLOps practices, automation, CI/CD, testing, and deployment workflows.
  • Participate in architecture discussions, code reviews, technical design, and documentation.
  • Stay current with emerging developments in AI, machine learning, LLMs, and intelligent automation.

WHAT MAKES YOU A GREAT FIT

  • 5+ years of experience in AI/ML engineering, machine learning, data science, or a related technical field.
  • Strong programming skills in Python and experience building production-quality software.
  • Strong understanding of machine learning algorithms, model development, evaluation, and optimisation.
  • Hands-on experience with Generative AI, LLMs, NLP, or modern AI frameworks is highly desirable.
  • Experience working with large datasets, data pipelines, feature engineering, and data processing.
  • Strong experience with machine learning frameworks such as PyTorch, TensorFlow, Scikit-learn, or equivalent.
  • Experience developing and deploying ML models in production environments.
  • Good understanding of REST APIs, microservices, databases, and scalable software architecture.
  • Experience with cloud platforms such as AWS, Azure, or GCP is preferred.
  • Familiarity with Docker, Kubernetes, CI/CD, MLOps, and model monitoring is an advantage.
  • Strong analytical and problem-solving skills with the ability to work on complex and ambiguous problems.
  • Ability to translate business requirements into practical and scalable AI/ML solutions.
  • Strong understanding of software engineering practices, Git, testing, debugging, and code quality.
  • Excellent communication and collaboration skills.
  • Ability to work independently, take ownership of technical initiatives, and mentor junior engineers.
  • Strong curiosity and willingness to experiment with emerging AI technologies and continuously improve technical solutions
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