What are the responsibilities and job description for the Sr. AI/ML Develope position at Primus Software Corporation?
Job Description
Job Description
Hello Professionals,
We are hiring for AI / ML Developer for one of our client
Sr. AI / ML Developer
Location : New York City, NY ..Hybrid / Onsite from day 1
Position Summary :
As an AI / ML Developer, you will be responsible for building, testing, and deploying AI / ML models that can analyze and interpret complex data sets, and enable predictive insights. You'll work closely with our product development, data science, and engineering teams to create solutions that deliver real-world impact.
Key Responsibilities :
Develop and implement AI / ML models : Design, develop, test, and deploy machine learning models that solve real-world problems. You'll handle data preprocessing, model training, tuning, and evaluation.
Data Exploration and Analysis : Work with structured and unstructured data to prepare it for ML models. Collaborate with data engineers to ensure high data quality and availability.
Model Optimization : Optimize algorithms to ensure high accuracy and low latency. Use techniques like hyperparameter tuning, regularization, and transfer learning.
Collaborate Across Teams : Work with product managers, engineers, and data scientists to integrate AI solutions into the company's offerings. Provide technical expertise and share knowledge with team members.
Maintain and Update Models : Monitor the performance of deployed models, make improvements as needed, and ensure their reliability and scalability.
Stay Updated : Keep up with the latest AI / ML advancements, tools, and libraries to bring innovative approaches to the team.
Qualifications :
Education : Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field.
Experience : Minimum of 7 years of experience in AI / ML model development, deployment, and optimization.
Technical Skills :
Proficiency in Python, R, or similar programming languages.
Experience with machine learning libraries like TensorFlow, PyTorch, Scikit-learn, etc.
Strong knowledge of ML algorithms, including supervised, unsupervised, and reinforcement learning.
Familiarity with cloud platforms (AWS, Azure, Google Cloud) for deploying models.
Understanding of data preprocessing techniques and experience with SQL and NoSQL databases.
Analytical Skills : Excellent problem-solving skills and a data-driven mindset.
Communication : Ability to explain technical concepts to non-technical stakeholders effectively.
Preferred Qualifications :
Experience with natural language processing, computer vision, or recommendation systems.
Familiarity with big data technologies (e.g., Spark, Hadoop) and data visualization tools.
Understanding of MLOps and experience with tools like MLflow or Kubeflow.
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