Founding ML enginner

This role is for one of the Weekday's clients

Min Experience: 2+ years

Location: NCR
JobType: full-time

We are looking for a highly motivated and entrepreneurial Founding Machine Learning Engineer with 2–5 years of hands-on experience in Machine Learning to join our early-stage engineering team. This is a high-impact opportunity for an engineer who enjoys solving complex problems, working with ambiguity, and taking ML products from concept to production.

As one of the founding members of the ML team, you will work closely with engineering and product stakeholders to design, build, train, evaluate, and deploy machine learning systems. You will have significant ownership over technical decisions and will play a key role in shaping the company's ML architecture, engineering practices, and product roadmap.

• Design, develop, train, and deploy machine learning models for real-world product and business problems.
• Translate complex business requirements into scalable and measurable ML solutions.
• Work with large and diverse datasets to perform data preprocessing, feature engineering, model development, and evaluation.
• Select appropriate algorithms, architectures, and modeling approaches based on the problem, data, and performance requirements.
• Build robust ML pipelines covering data preparation, experimentation, training, validation, deployment, and monitoring.
• Optimize models for accuracy, latency, scalability, reliability, and computational efficiency.
• Conduct experiments, analyze model performance, and continuously improve ML systems based on quantitative results.
• Collaborate closely with software engineers to integrate machine learning models into production applications and APIs.
• Establish best practices around model versioning, reproducibility, testing, monitoring, and deployment.
• Stay current with advancements in machine learning and evaluate emerging techniques that can create meaningful product advantages.
• Take end-to-end ownership of ML projects, from initial experimentation through production deployment and iteration.

• 2–5 years of professional experience in Machine Learning or a closely related engineering role.
• Strong understanding of core Machine Learning concepts, including supervised and unsupervised learning, classification, regression, clustering, model evaluation, and optimization.
• Strong proficiency in Python and experience with ML libraries such as scikit-learn, PyTorch, or TensorFlow.
• Hands-on experience building, training, evaluating, and deploying machine learning models.
• Strong knowledge of data preprocessing, feature engineering, model selection, and hyperparameter tuning.
• Solid understanding of statistics, probability, linear algebra, and optimization fundamentals relevant to machine learning.
• Experience working with structured and/or unstructured datasets.
• Strong problem-solving and analytical skills with the ability to independently investigate and resolve challenging ML problems.
• Experience taking ML models from experimentation to production environments.
• Familiarity with software engineering fundamentals, Git, APIs, testing, and scalable system design.

• Experience with deep learning, NLP, computer vision, recommendation systems, or time-series modeling.
• Exposure to Generative AI, LLMs, embeddings, vector databases, or RAG systems.
• Experience with cloud platforms such as AWS, GCP, or Azure.
• Familiarity with Docker, Kubernetes, MLflow, or other MLOps tools.
• Experience working in an early-stage startup or high-ownership engineering environment.