AI / ML Engineer (Remote) - Contractual (3 months)

We are looking for a Machine Learning Engineer to build efficient, data-driven artificial intelligence systems that advance our predictive automation capabilities. The candidate should be highly skilled in statistics and programming, with the ability to confidently assess, analyze, and organize large amounts of data. The candidate should also be able to execute tests and optimize machine-learning models and algorithms. The ideal candidate will have a strong background in machine learning, data science, and software development and will work closely with our product, data science, and engineering teams to develop, deploy, and maintain machine learning models that drive our vision.

Responsibilities

Designing, developing, testing, and deploying machine learning models for various applications

Collaborating with data scientists, software engineers, and product managers to develop data-driven features

Optimizing and improving the performance of existing machine learning models

Implementing and maintaining scalable machine learning pipelines and infrastructure

Analyzing and preprocessing large datasets to extract valuable insights and features

Staying updated with the latest developments in machine learning, deep learning, and related technologies

Conducting model training, validation, and performance evaluation to ensure models meet the required accuracy and reliability

Creating and maintaining documentation related to machine learning models, algorithms, and processes

Developing A / B testing frameworks and managing the deployment of models in production

Qualifications

Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, Statistics, or a related field

3+ years of experience in AI and Machine learning

1+ years of experience in GenAI

Proven experience as a Machine Learning Engineer, Data Scientist, or in a similar role

Strong programming skills in Python, R, or similar languages

Proficiency with machine learning libraries and frameworks such as TensorFlow, PyTorch, scikit learn, etc and experience with NLP libraries (e.g., NLTK, spaCy, Hugging Face Transformers)

Experience with data preprocessing, data wrangling, and data visualization

Hands-on experience with SQL databases and API integration

Experience with text generation techniques, including language models like GPT

Hands-on experience with cloud platforms (AWS, GCP, or Azure) and deploying models in production

Solid understanding of machine learning algorithms, deep learning architectures, and statistical methods

Experience with version control systems (e.g., Git) and continuous integration / continuous deployment (CI / CD) pipelines

Ability to work in a collaborative environment and communicate effectively with cross-functional teams

Nice-to-Have

Knowledge of natural language processing (NLP) and its applications

Experience with MLOps tools and best practices for scalable model deployment and monitoring

Familiarity with data privacy and security regulations

Experience with real-time data processing and streaming technologies

Experience with reinforcement learning, generative models, or unsupervised learning techniques