AIML Engineer – Python, Cloud Deployment & Data Modeling

Job Summary

Synechron is seeking a skilled AI/ML Engineer to develop deploy and maintain scalable machine learning models that enable data-driven insights and innovative business this role you will work closely with data scientists software engineers and product teams to deliver end-to-end AI applications within a cloud ecosystem. Your expertise will support our strategic initiatives in automation predictive analytics and intelligent system integration by creating robust efficient and scalable AI/ML solutions that add measurable value to our clients and internal operations.

Software Requirements

Required Skills:

• Strong proficiency in Python (version 3.7) with experience in developing training and deploying machine learning models

• Basic familiarity with TensorFlow or PyTorch for model development and training

• Data manipulation libraries: Pandas NumPy

• Version control systems: Git

• Experience utilizing cloud AI/ML services (AWS Azure GCP) for training tuning and deploying models

• REST API development for model integration into applications

• Model deployment and containerization experience with Docker

• Working knowledge of cloud deployment practices security and scalability

Preferred Skills:

• Experience with cloud-specific ML platforms such as AWS SageMaker Azure AI or GCP Vertex AI

• Familiarity with NLP frameworks and techniques including transformers (e.g. Hugging Face) and spaCy

• Additional Python libraries related to deep learning and NLP (e.g. transformers)

Overall Responsibilities

• Design develop validate and optimize machine learning models tailored for predictive analytics automation and classification tasks

• Prepare and preprocess large datasets performing feature engineering to maximize model effectiveness

• Deploy models into production environments ensuring seamless integration via REST APIs and enterprise applications

• Collaborate with data scientists software engineers and stakeholders to define requirements and deliver scalable AI solutions

• Utilize cloud services for model training hyperparameter tuning and deployment maintaining high performance and security standards

• Document workflows maintain version control and ensure reproducibility of experiments for ongoing improvements

• Monitor model performance troubleshoot issues promptly and refine models based on real-world data feedback

• Stay current with emerging AI/ML technologies incorporating innovative techniques to enhance solutions and workflows

Technical Skills (By Category)

Programming Languages:

• Required: Python (3.7) with experience in ML libraries

• Preferred: Additional experience in R Scala or other relevant languages

Data Management & Processing:

• Pandas NumPy for data transformation and feature engineering

• Understanding of large data storage solutions and data pipeline integration

Cloud Technologies:

• AWS Azure or GCP for training deployment and management of models

• Familiarity with cloud storage compute resources and security best practices

Frameworks & Libraries:

• TensorFlow or PyTorch (basic proficiency)

• NLP: Hugging Face Transformers spaCy (preferred)

Development & Deployment Tools:

• Git for version control

• Docker for containerization

• CI/CD pipelines using Jenkins Azure DevOps or similar tools

Security & Compliance:

• Basic understanding of data privacy security protocols and relevant regulations

Experience Requirements

• 3 to 12 years of professional experience in AI/ML model development training and deployment

• Proven track record of operationalizing machine learning models in production environments

• Experience applying AI/ML techniques for predictive analytics NLP or automation projects

• Exposure to cloud-based AI solutions scalable infrastructure and container orchestration is highly desirable

• Industry experience in finance healthcare technology or related sectors is a plus

• Equivalent practical experience or project-based work demonstrating relevant skills is acceptable

Day-to-Day Activities

• Collaborate with data scientists and software teams to translate business needs into machine learning models and pipelines

• Develop train and tune models optimizing hyperparameters for accuracy and efficiency

• Prepare datasets through cleaning feature engineering and transformation processes

• Deploy models into cloud environments creating REST APIs for integration with applications

• Monitor deployed models for performance and drift troubleshooting issues proactively

• Refine models based on feedback and changing data patterns

• Document processes workflows and deployment procedures to ensure reproducibility

• Engage in research on emerging AI/ML techniques and incorporate applicable innovations into projects

• Participate in agile ceremonies code reviews and knowledge sharing activities

Qualifications

• Bachelors or Masters degree in Computer Science Data Science Engineering or related field; higher qualifications or certifications are advantageous

• Certifications such as AWS Certified Machine Learning Specialty GCP Professional ML Engineer or equivalent are preferred

• Proven experience with AI/ML model deployment in enterprise or production environments

• Commitment to continuous learning staying updated with evolving AI/ML methods and cloud technologies

Professional Competencies

• Strong analytical and problem-solving skills with attention to detail in model development and performance evaluation

• Excellent communication skills to articulate complex technical concepts to diverse audiences

• Ability to collaborate effectively with multidisciplinary teams and stakeholders

• Self-driven learner committed to continuous professional growth and technology adoption

• Results-oriented focus on delivering scalable reliable and impactful AI solutions

• Adaptability to evolving project requirements and emerging AI/ML trends

SYNECHRONS DIVERSITY & INCLUSION STATEMENT

Diversity & Inclusion are fundamental to our culture and Synechron is proud to be an equal opportunity workplace and is an affirmative action employer. Our Diversity Equity and Inclusion (DEI) initiative Same Difference is committed to fostering an inclusive culture promoting equality diversity and an environment that is respectful to all. We strongly believe that a diverse workforce helps build stronger successful businesses as a global company. We encourage applicants from across diverse backgrounds race ethnicities religion age marital status gender sexual orientations or disabilities to apply. We empower our global workforce by offering flexible workplace arrangements mentoring internal mobility learning and development programs and more.

All employment decisions at Synechron are based on business needs job requirements and individual qualifications without regard to the applicants gender gender identity sexual orientation race ethnicity disabled or veteran status or any other characteristic protected by law.

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