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Job Description

Job Title: GenAI Engineer


Overview:


We are seeking an experienced GenAI Engineer with 3 to 6 years of expertise in developing and deploying generative AI models and applications. The ideal candidate will be responsible for implementing advanced AI solutions, working closely with data scientists and software engineers to enhance analytics capabilities within the organization.


Overall Responsibilities:
  • Design, develop, and implement generative AI solutions tailored to financial analytics and investment strategies.
  • Collaborate with data scientists to refine and validate AI models for operational efficiency.
  • Manage the entire project lifecycle, from concept through deployment and monitoring of AI applications.
  • Conduct thorough testing and evaluation of generative models to ensure robustness and accuracy.
  • Provide technical documentation detailing methodologies and project outcomes for internal stakeholders.
  • Stay current with the latest developments in AI technology and methodologies, integrating relevant advancements into existing systems.
Technical Skills:

1. Software Requirements:


  • Proficiency in programming languages such as Python, R, or Julia, with a focus on AI frameworks (TensorFlow, PyTorch).
  • Experience with cloud platforms (AWS, Azure, or Google Cloud) for model deployment and data storage.

2. Generative AI Expertise:


  • Hands-on experience with generative models (e.g., GANs, VAEs) and algorithms.
  • Ability to design and optimize AI models for financial applications.

3. Data Handling:


  • Strong skills in data preprocessing, feature engineering, and exploratory data analysis.
  • Proficiency in SQL and experience with large datasets.

4. DevOps Practices:


  • Familiarity with CI/CD pipelines and version control systems (e.g., Git) for collaborative coding and project management.
Experience:
  • 3 to 6 years of experience in developing and deploying AI solutions, preferably within the financial domain.
  • Previous role in a data-driven environment with a focus on analytics and reporting.
Day-to-Day Activities:
  • Collaborate with teams to identify user needs and refine project requirements for generative models.
  • Develop and deploy generative models and architectures to solve complex problems.
  • Monitor performance of AI applications and provide ongoing enhancements based on performance metrics.
  • Document methodologies, processes, and model designs for institutional knowledge.
  • Participate in code reviews and provide mentorship to junior engineers and interns.
Qualifications:
  • Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, or a related field.
  • Relevant certifications in AI or data science are advantageous.
Soft Skills:
  • Strong analytical and problem-solving skills, with the ability to think critically and creatively.
  • Excellent verbal and written communication skills to convey complex AI concepts to non-technical stakeholders.
  • Ability to work well independently and collaboratively across interdisciplinary teams.
  • Strong organizational skills and attention to detail.
  • Adaptability to a fast-paced work environment with evolving technologies.

S​YNECHRON’S 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 applicant’s gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law.


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