Job Summary
We are looking for a Machine Learning Engineer (AI/ML) with 3-5 years of experience to develop and deploy scalable AI models. The ideal candidate has hands-on experience with machine learning algorithms, deep learning frameworks, and cloud-based ML solutions. You will work on real-world AI applications, optimize ML models, and collaborate with data scientists, software engineers, and product teams to deliver AI-powered solutions.
Key Responsibilities
- Develop, train, and deploy ML models for applications in NLP, computer vision, recommendation systems, or predictive analytics.
- Design and implement ML pipelines for model training, validation, and deployment.
- Preprocess and analyze large datasets to extract meaningful insights and improve model performance.
- Optimize and fine-tune ML models using techniques like feature engineering, hyperparameter tuning, and distributed training.
- Deploy ML models in production using MLOps best practices with cloud platforms (GCP, AWS, or Azure).
- Collaborate with cross-functional teams to integrate AI models into production systems.
- Monitor and maintain deployed models, ensuring their performance and retraining when necessary.
- Stay up-to-date with industry trends, emerging AI/ML technologies, and best practices.
- Bachelor’s or Master’s degree in Computer Science, Data Science, AI, or a related field.
- 3-5 years of experience in machine learning, AI, or data science roles.
- Strong programming skills in Python (TensorFlow, PyTorch, Scikit-learn, Pandas, NumPy).
- Experience in building and deploying ML models on cloud platforms (Google Cloud Platform, AWS, or Azure).
- Hands-on experience with ML algorithms (classification, regression, clustering, reinforcement learning).
- Familiarity with deep learning architectures (CNNs, RNNs, Transformers, GANs).
- Understanding of MLOps practices (CI/CD pipelines, model monitoring, and retraining).
- Experience working with large-scale datasets using SQL, BigQuery, or Spark.
- Knowledge of containerization and orchestration using Docker and Kubernetes.
Discover some of the global benefits that empower our people to become the best version of themselves:
- Finance: Competitive salary package, share plan, company performance bonuses, value-based recognition awards, referral bonus;
- Career Development: Career coaching, global career opportunities, non-linear career paths, internal development programmes for management and technical leadership;
- Learning Opportunities: Complex projects, rotations, internal tech communities, training, certifications, coaching, online learning platforms subscriptions, pass-it-on sessions, workshops, conferences;
- Work-Life Balance: Hybrid work and flexible working hours, employee assistance programme;
- Health: Global internal wellbeing programme, access to wellbeing apps;
- Community: Global internal tech communities, hobby clubs and interest groups, inclusion and diversity programmes, events and celebrations.
At Endava, we’re committed to creating an open, inclusive, and respectful environment where everyone feels safe, valued, and empowered to be their best. We welcome applications from people of all backgrounds, experiences, and perspectives—because we know that inclusive teams help us deliver smarter, more innovative solutions for our customers. Hiring decisions are based on merit, skills, qualifications, and potential. If you need adjustments or support during the recruitment process, please let us know.
