AI/ML Engineer (Artificial Intelligence & Machine Learning)
Job Title: AI/ML Engineer (Artificial Intelligence & Machine Learning) Job Type: Full-Time / Contract Experience Level: Mid-Level to Senior Location: [Insert Location or Remote] Job Summary We are seeking a skilled AI/ML Engineer to design, develop, and deploy artificial intelligence and machine learning solutions that solve complex business problems. The ideal candidate will have experience building machine learning models, developing AI-powered applications, and working with large datasets to deliver scalable, high-performance solutions. The successful candidate will collaborate with software engineers, data scientists, product managers, and business stakeholders to develop intelligent systems that improve automation, decision-making, and operational efficiency.
Key Responsibilities
Design, develop, train, and deploy machine learning models and AI applications. Build and optimize predictive analytics, natural language processing (NLP), and generative AI solutions. Develop AI-powered applications using large language models (LLMs), retrieval-augmented generation (RAG), and related technologies. Collect, clean, process, and analyze large datasets for model training and evaluation. Implement machine learning pipelines and automate model deployment and monitoring. Integrate AI/ML models into existing applications, APIs, and cloud-based platforms. Evaluate model performance, accuracy, scalability, and reliability. Collaborate with cross-functional teams to identify AI opportunities and translate business requirements into technical solutions. Follow best practices for data security, responsible AI, model governance, and bias mitigation. Stay current with emerging AI/ML frameworks, tools, and industry developments.
Required Qualifications
Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, Engineering, or a related field, or equivalent practical experience. 3+ years of experience in machine learning, artificial intelligence, data science, or software engineering. Strong programming experience with Python. Experience with machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn. Knowledge of supervised and unsupervised learning, deep learning, model training, and evaluation. Experience working with SQL, databases, and data processing pipelines. Familiarity with REST APIs, cloud computing, and production software development. Understanding of algorithms, statistics, data structures, and software engineering principles.
Preferred Qualifications
Experience with generative AI, LLMs, prompt engineering, and RAG architectures. Familiarity with AI development tools and frameworks such as Hugging Face, LangChain, or LlamaIndex. Experience with AWS, Microsoft Azure, or Google Cloud Platform. Knowledge of MLOps tools and practices, including MLflow, Docker, Kubernetes, and CI/CD pipelines. Experience with vector databases such as Pinecone, Weaviate, or Milvus. Familiarity with data engineering tools such as Apache Spark, Kafka, or Airflow. Experience deploying and monitoring AI solutions in production environments. Key Skills Python programming Machine learning and deep learning Generative AI and large language models Natural language processing Data analysis and model optimization Cloud-based AI development MLOps and model deployment Problem-solving and analytical thinking Communication and cross-functional collaboration Success Metrics Accuracy, reliability, and performance of deployed models. Successful integration of AI solutions into business applications. Reduction in manual processes through automation. Improved operational efficiency and measurable business outcomes. Scalability, maintainability, and responsible use of AI systems.