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.ResponsibilitiesDesigning, developing, testing, and deploying machine learning models for various applicationsCollaborating with data scientists, software engineers, and product managers to develop data-driven featuresOptimizing and improving the performance of existing machine learning modelsImplementing and maintaining scalable machine learning pipelines and infrastructureAnalyzing and preprocessing large datasets to extract valuable insights and featuresStaying updated with the latest developments in machine learning, deep learning, and related technologiesConducting model training, validation, and performance evaluation to ensure models meet the required accuracy and reliabilityCreating and maintaining documentation related to machine learning models, algorithms, and processesDeveloping A / B testing frameworks and managing the deployment of models in productionQualificationsBachelor's or Master's degree in Computer Science, Data Science, Machine Learning, Statistics, or a related field3+ years of experience in AI and Machine learning1+ years of experience in GenAIProven experience as a Machine Learning Engineer, Data Scientist, or in a similar roleStrong programming skills in Python, R, or similar languagesProficiency 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 visualizationHands-on experience with SQL databases and API integrationExperience with text generation techniques, including language models like GPTHands-on experience with cloud platforms (AWS, GCP, or Azure) and deploying models in productionSolid understanding of machine learning algorithms, deep learning architectures, and statistical methodsExperience with version control systems (e.g., Git) and continuous integration / continuous deployment (CI / CD) pipelinesAbility to work in a collaborative environment and communicate effectively with cross-functional teamsNice-to-HaveKnowledge of natural language processing (NLP) and its applicationsExperience with MLOps tools and best practices for scalable model deployment and monitoringFamiliarity with data privacy and security regulationsExperience with real-time data processing and streaming technologiesExperience with reinforcement learning, generative models, or unsupervised learning techniques