AI ML engineer

Job Summary:

We are seeking a highly skilled Senior AI/ML Engineer to join our dynamic team. The

ideal candidate will have extensive experience in designing, building, and deploying

machine learning models and AI solutions to solve real-world business challenges. You

will collaborate with cross-functional teams to create scalable, efficient AI/ML systems,

ensuring their seamless integration into production environments.

Key Responsibilities:

? Lead the design, development, and deployment of machine learning models for

various use cases such as recommendation systems, computer vision, natural

language processing (NLP), and predictive analytics.

? Work with large datasets to build, train, and optimize models using techniques

such as classification, regression, clustering, and neural networks. ? Fine-tune

pre-trained models and develop custom models based on specific business

needs.

? Collaborate with data engineers to build scalable data pipelines and ensure the

smooth integration of models into production.

? Implement model monitoring and maintenance strategies to ensure performance,

accuracy, and continuous improvement of deployed models.

? Utilize cloud platforms (AWS, GCP, Azure) to deploy, manage, and scale AI/ML

solutions.

? Stay up-to-date with the latest advancements in AI/ML research, and apply

innovative techniques to improve existing systems.

? Communicate effectively with stakeholders to understand business requirements

and translate them into AI/ML-driven solutions.

? Document processes, methodologies, and results for future reference and

reproducibility.

Key Skills & Qualifications:

? Experience: 6+ years of experience in AI/ML engineering roles, with a proven

track record of successfully delivering machine learning projects.

? AI/ML Expertise: Strong knowledge of machine learning algorithms (supervised,

unsupervised, reinforcement learning) and AI techniques, including NLP,

computer vision, and recommendation systems.

? Programming Languages: Proficient in Python and relevant ML libraries such

as TensorFlow, PyTorch, Scikit-learn, and Keras.

? Data Manipulation: Experience with data manipulation libraries such as Pandas,

NumPy, and SQL for managing and processing large datasets.

? Model Development: Expertise in building, training, deploying, and fine-tuning

machine learning models in production environments.

? Cloud Platforms: Experience with cloud platforms such as AWS, GCP, or Azure

for the deployment and scaling of AI/ML models.

? MLOps: Knowledge of MLOps practices for model versioning, automation, and

monitoring.

? Data Preprocessing: Proficient in data cleaning, feature engineering, and

preparing datasets for model training.

? NLP & Computer Vision: Hands-on experience with natural language

processing or computer vision projects.

? Big Data: Familiarity with big data tools and frameworks (e.g., Apache Spark,

Hadoop) is an advantage.

? Problem-Solving Skills: Strong analytical and problem-solving abilities, with a

focus on delivering practical AI/ML solutions.

? Generative AI & Agentic AI Proficiency: Demonstrated expertise in

Generative AI, Large Language Models (LLMs), and Agentic AI, with practical

experience in developing Retrieval-Augmented Generation (RAG)-based

chatbots and agentic tools.

? API Development & Frameworks: Extensive hands-on experience in

designing and implementing APIs, utilizing frameworks such as Flask or

FastAPI to build robust and efficient applications.