Machine Learning Engineer

Job Title Machine Learning Engineer Job Summary We are seeking a talented and innovative Machine Learning Engineer to design, develop, deploy, and maintain machine learning models and AI-powered solutions. The ideal candidate will work closely with data scientists, software engineers, and business stakeholders to build scalable machine learning systems that solve complex business problems and drive data-driven decision-making. Key Responsibilities • Design, develop, train, and deploy machine learning models and algorithms. • Build scalable data pipelines for data collection, processing, and feature engineering. • Evaluate and optimize machine learning models for accuracy, performance, and scalability. • Collaborate with cross-functional teams to understand business requirements and translate them into AI/ML solutions. • Deploy and monitor machine learning models in production environments. • Perform model validation, testing, and performance tuning. • Develop and maintain MLOps workflows for continuous integration and deployment of ML models. • Analyze large datasets to identify trends, patterns, and opportunities for predictive analytics. • Research and implement emerging AI and machine learning technologies. • Document model architectures, processes, and technical solutions. Required Skills • Strong understanding of Machine Learning, Deep Learning, and Artificial Intelligence concepts. • Experience with supervised and unsupervised learning algorithms. • Knowledge of data preprocessing, feature engineering, and model evaluation techniques. • Strong analytical and problem-solving abilities. • Experience deploying machine learning solutions into production. • Excellent communication and collaboration skills. Technical Skills • Programming Languages: Python, R, Java • Machine Learning Libraries: Scikit-learn, TensorFlow, PyTorch, Keras • Data Processing: Pandas, NumPy, Apache Spark • Databases: MySQL, PostgreSQL, MongoDB • Cloud Platforms: AWS, Azure, Google Cloud Platform (GCP) • MLOps Tools: MLflow, Kubeflow, Airflow • Version Control: Git, GitHub, GitLab • Containerization: Docker, Kubernetes • Data Visualization: Matplotlib, Seaborn, Power BI, Tableau Qualifications • Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, Statistics, Mathematics, or a related field. • Relevant AI/ML certifications are a plus. Experience • 3-7 years of experience in Machine Learning, Data Science, or AI-related roles. • Hands-on experience building and deploying machine learning models in production environments. • Experience working with large-scale datasets and distributed computing frameworks. • Familiarity with Agile development methodologies. Preferred Qualifications • Experience with Generative AI, Large Language Models (LLMs), and Natural Language Processing (NLP). • Knowledge of Computer Vision and Deep Learning frameworks. • Experience with Retrieval-Augmented Generation (RAG) architectures. • Familiarity with vector databases such as Pinecone, Weaviate, or ChromaDB. • Experience integrating AI services through APIs and cloud-based AI platforms. Preferred Qualities • Strong problem-solving and critical-thinking skills. • Passion for innovation and emerging AI technologies. • Ability to work independently and in a collaborative environment. • Excellent communication and presentation skills. • Commitment to continuous learning and professional development. Employment Type Full-Time Location: Nice To Have Remote / Hybrid / On-site (based on company requirements) • Experience with Generative AI tools such as OpenAI APIs, Claude, Gemini, or similar platforms. • Knowledge of LLM fine-tuning, prompt engineering, and AI model evaluation. • Experience building AI-powered chatbots, recommendation engines, or predictive analytics solutions. • Contributions to open-source AI/ML projects or published research in machine learning.