Artificial Intelligence/Machine Learning Engineer
3 weeks ago
We have a Job Opportunity for you with Client,
Job - AI ML Engineer
About Client - We are a preferred and trusted Technology Consulting and Development Partner for global enterprises, from start-ups to Fortune 500s. Work with different stakeholders of the knowledge value chain to provide the Business Intelligence, Data Analytics and Technology solutions which enables them to make the informed decisions and solve the business challenges.
Our Services include Business Intelligence, Data Analytics, Data Visualization, Artificial Intelligence, Power BI Services, Power Apps, Power Automate, Product Development, Generative AI, Low-Code/No-Code, Microsoft Fabric. We have been in the market for the last 10 successful & progressive years with 100+ successful delivery of projects. Cient started its regional office in the USA in 2023. It has an extensive Global Experience & Capabilities to provide Technology support in a major part of the world.
About the Role :
We are seeking a highly skilled AI/ML Engineer to join our client's team in the USA. The ideal candidate will be responsible for designing, developing, and deploying machine learning models and AI-driven solutions. You will collaborate with data scientists, software engineers, and business stakeholders to create intelligent systems that drive business value.
Key Responsibilities :
Model Development & Deployment :
- Design, develop, and implement machine learning models for various use cases (NLP, Computer Vision, Recommendation Systems, etc.).
- Train, fine-tune, and optimize deep learning models using frameworks like TensorFlow, PyTorch, or Scikit-learn.
- Deploy and integrate ML models into production environments using cloud services (AWS, GCP, Azure) and MLOps best practices.
Data Processing & Feature Engineering :
- Collect, clean, and preprocess structured and unstructured data for training ML models.
- Perform feature selection, transformation, and dimensionality reduction to improve model performance.
- Work with large datasets, using tools like Pandas, NumPy, and SQL.
AI Model Evaluation & Optimization :
- Conduct rigorous model evaluation and testing to ensure accuracy, fairness, and robustness.
- Implement hyperparameter tuning and optimization techniques.
- Utilize A/B testing and real-world validation methods for continuous model improvements.
Scalability & Performance Enhancement :
- Optimize algorithms for real-time inference and large-scale data processing.
- Utilize cloud-based AI/ML services for scalable deployment.
- Work with distributed computing frameworks like Spark, Ray, or Dask.
Collaboration & Innovation :
- Work closely with cross-functional teams, including data scientists, engineers, and product managers, to align AI/ML solutions with business goals.
- Stay updated with the latest advancements in AI/ML and contribute to research and development initiatives.
Required Skills & Qualifications :
Educational Background :
- Bachelor's/Master's/PhD in Computer Science, Machine Learning, Artificial Intelligence, or related field.
Technical Skills :
- Programming : Proficiency in Python (TensorFlow, PyTorch, Scikit-learn), and familiarity with Java or C++.
- Machine Learning & Deep Learning : Strong understanding of ML algorithms, deep learning architectures (CNNs, RNNs, Transformers), and statistical modeling.
- Big Data & Cloud : Experience with AWS (SageMaker, Lambda), GCP (Vertex AI), or Azure (Machine Learning Studio).
- MLOps : Experience with ML model deployment, monitoring, and CI/CD pipelines using Docker, Kubernetes, and Git.
- Data Handling : Strong experience with SQL, NoSQL, and data pipeline frameworks like Apache Spark.
Soft Skills :
- Strong problem-solving skills with a keen eye for detail.
- Excellent communication skills to convey complex AI/ML concepts to non-technical stakeholders.
- Ability to work independently and collaboratively in a fast-paced environment.
Preferred Qualifications :
- Experience with Generative AI models (GPT, DALL-E, Stable Diffusion).
- Familiarity with edge AI and deploying models on mobile/embedded devices.
- Contributions to AI/ML open-source projects or research publications.
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