Senior Software Engineer - Machine Learning / AI Engineer
Weekday AI Bengaluru, Karnataka, India
Technology, Information and Internet · 11-50 employees
About the role
Design, develop, and maintain scalable machine learning and AI systems for real-world applications. Collaborate with cross-functional teams to integrate AI/ML capabilities into production-ready software products.
What they look for
Requirements
Requires 5-10 years of professional experience in software engineering and machine learning. Candidates must possess strong programming skills in Python and hands-on experience with ML frameworks and cloud infrastructure.
Full description
This role is for one of Weekday’s clients Salary range: Rs 5000000 - Rs 20000000 (ie INR 50 - 200 LPA)
Min Experience: 5+ years Location: Bengaluru, Karnataka JobType: full-time
We are looking for a highly skilled Senior Software Engineer – Machine Learning / AI Engineer with 5–10 years of experience to design, develop, and deploy intelligent, scalable, and production-ready AI/ML solutions. The ideal candidate will combine strong software engineering fundamentals with expertise in machine learning, artificial intelligence, experimentation, and system design.
You will work closely with engineering, product, data, security, cloud infrastructure, and design teams to translate complex business and technical challenges into robust AI-powered products. This role is ideal for someone who enjoys working across disciplines and can contribute from research and prototyping through production deployment and optimization.
Key Responsibilities• Design, develop, and maintain scalable machine learning and AI systems for real-world applications.
- Build and productionize ML models, algorithms, pipelines, APIs, and intelligent services.
- Research and evaluate emerging techniques across machine learning, deep learning, generative AI, NLP, computer vision, recommendation systems, or related areas.
- Develop efficient data and model pipelines covering data preparation, feature engineering, training, evaluation, deployment, monitoring, and continuous improvement.
- Optimize models and systems for accuracy, latency, scalability, reliability, and cost.
- Collaborate with software engineers to integrate AI/ML capabilities into production applications and distributed systems.
- Work with product managers and technical program teams to translate product requirements into measurable ML objectives and technical solutions.
- Partner with security and cloud/infrastructure teams to ensure AI systems meet requirements for privacy, security, reliability, and operational scalability.
- Conduct experiments, analyze results, establish evaluation frameworks, and communicate technical findings clearly.
- Mentor engineers, conduct technical reviews, establish engineering best practices, and contribute to architectural decisions.
- Stay current with advancements in AI/ML research, frameworks, infrastructure, and industry practices.
Required Qualifications• 5–10 years of professional experience in software engineering, machine learning, artificial intelligence, or a closely related field.
- Strong programming skills in Python and/or other modern programming languages such as Java, C++, Go, or Scala.
- Strong understanding of machine learning algorithms, statistics, data structures, algorithms, and software engineering principles.
- Hands-on experience building and deploying production-grade ML/AI systems.
- Experience with ML frameworks such as PyTorch, TensorFlow, Scikit-learn, or equivalent.
- Strong understanding of APIs, distributed systems, databases, version control, testing, and software development lifecycle.
- Experience working with cloud platforms, containerization, CI/CD, and scalable infrastructure.
- Strong analytical, problem-solving, communication, and collaboration skills.
Good-to-Have SkillsExperience or exposure to Machine Learning Engineer, AI Engineer, Research Scientist, Product Manager, Security Engineer, Cloud/Infrastructure Engineer, Technical Program Manager, or UX/Design leadership responsibilities will be highly valued. Familiarity with Generative AI, LLMs, RAG, MLOps, Kubernetes, Docker, AWS/Azure/GCP, model optimization, AI security, responsible AI, experimentation, product strategy, and human-centered AI/UX is a strong advantage.
What We OfferYou will have the opportunity to work on challenging AI/ML problems, influence technical architecture and product direction, collaborate with multidisciplinary teams, and help build intelligent systems that operate reliably at scale.
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