Job Description

Company Description

Technology is our how. And people are our why. For over two decades, we have been harnessing technology to drive meaningful change.



By combining world-class engineering, industry expertise and a people-centric mindset, we consult and partner with leading brands from various industries to create dynamic platforms and intelligent digital experiences that drive innovation and transform businesses.



From prototype to real-world impact - be part of a global shift by doing work that matters.

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.

Qualifications

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

.

Additional Information

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.