Machine Learning Engineer

Job Profile & DescriptionMachine Learning is a field of artificial intelligence that focuses on developing systems that canlearn and improve from experience. Machine Learning Engineers work on creating andimplementing AI models and algorithms to solve complex problems. This role often involvesworking with large datasets, developing algorithms, and deploying models into productionenvironments.We are seeking an enthusiastic and motivated Machine Learning Engineer with 1-3 years ofexperience to join our team. As a Machine Learning Engineer, you will be responsible fordesigning, building, and maintaining machine learning models with a focus on Generative AI,Large Language Models (LLMs), and Natural Language Processing (NLP). You will use your skills and knowledge to tackle real-world challenges and contribute to the advancement of AI technology.Duties and ResponsibilitiesDesign, develop, and implement efficient and scalable machine learning models and algorithms.Work closely with software engineers to integrate ML models into production systems.Implement and optimize ML algorithms and pipelines.Optimize and fine-tune existing models for improved performance.Contribute to the research and implementation of state-of-the-art GenAI techniques.Create AI agents designed to tackle real-life problems.Harness internal and external knowledge systems to enhance model intelligence.Participate in the full machine learning lifecycle, from data preparation to modeldeployment.Collaborate with cross-functional teams to identify and solve complex business problemsusing AI.Stay up-to-date with the latest advancements in ML, especially in GenAI, LLMs, andNLP.Document your work, including model architectures, experiments, and results.Must-Have Skills1-3 years of professional experience in machine learning engineering.Proficiency in designing and implementing machine learning models, particularly inGenAI, LLM, and NLP domains.Hands-on experience in developing and deploying agentic AI solutions to solvecomplex, real-world problems.Strong proficiency in Python and either PyTorch or TensorFlow for building and trainingmodels.Strong programming skills in Python, including knowledge of data structures, algorithms,and object-oriented programming principles.Experience with NLP techniques and frameworks (e.g., NLTK, spaCy, Hugging FaceTransformers).Familiarity with GenAI and LLM technologies (e.g., GPT, Llama, Mistral).Strong problem-solving skills and ability to translate business requirements into technicalsolutions.Proficiency in version control systems (e.g., Git).Good-to-Have SkillsExperience in writing SQL queries and working with relational databases.Experience in integrating or productionising machine learning models to the existingframeworks.Experience in back-end development to integrate machine learning models withapplications (Full stack experience is an extra bonus to have).Experience with data engineering tools and techniques for large-scale data processing.Experience with cloud platforms (e.g., AWS, GCP, or Azure) for ML model deployment.Understanding of serving technologies (e.g., FastAPI, Flask API, ONNX Runtime).Familiarity with ML experiment tracking tools (e.g., MLflow, Weights & Biases).Strong desire to stay updated with the latest advancements in machine learning and AI.Familiarity with Kubernetes, Docker, and Jenkins for model deployment and pipelineautomation.