Sr. Machine Learning Engineer (1764)

Overview:

The Sr. Machine Learning Engineer will drive our AI initiatives by designing, building, and deploying advanced ML solutions that power business growth and innovation at scale. You’ll lead complex projects, mentor peers, and collaborate with global teams to deliver production-ready AI/ML systems that make a measurable business impact.

Prodege:

A cutting-edge marketing and consumer insights platform, Prodege has charted a course of innovation in the evolving technology landscape by helping leading brands, marketers, and agencies uncover the answers to their business questions, acquire new customers, increase revenue, and drive brand loyalty & product adoption. Bolstered by a major investment by Great Hill Partners in Q4 2021 and strategic acquisitions of Pollfish, BitBurst & AdGate Media in 2022, Prodege looks forward to more growth and innovation to empower our partners to gather meaningful, rich insights and better market to their target audiences.

As an organization, we go the extra mile to “Create Rewarding Moments” every day for our partners, consumers, and team. Come join us today!

*** Seeking Qualified Candidates for this Remote role. Applicants must reside in the continental United States. ***

Primary Objectives: 

• Advanced AI/ML Solution Development
• Leading Model Research and Development
• Strategic Cross-functional Collaboration
• Industry Trend Analysis and Application
• AI Technique Evaluation and Innovation
• Model Training, Validation, and Optimization
• Seamless Integration and Performance Monitoring
• Mentorship and Advanced Team Support

Qualifications - To perform this job successfully, an individual must be able to perform each job duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

Detailed Job Duties: 

• Develop and implement advanced AI/ML solutions aligned with strategic company goals.
• Lead the research, development, and deployment of sophisticated AI/ML models using Python,
• LangChain, LLMs, and HuggingFace transformers, as well as libraries for Deep Learning (e.g.,
• Pytorch), ML libraries (e.g., XGBoost, Scikit-learn), and NLP (e.g., spaCy, NLTK).
• Fine-tune existing models and create new models from scratch to enhance business processes and outcomes.
• Collaborate cross-functionally with senior teams to identify opportunities for AI/ML integration and optimization.
• Stay abreast of and apply industry trends and advancements to ensure our AI initiatives remain innovative and impactful.
• Research, evaluate, and implement advanced AI techniques and tools to inform decision-making.
• Collaborate with senior data and software engineers and other stakeholders to ensure seamless integration of AI/ML solutions.
• Monitor and optimize model performance on a regular basis.
• Provide advanced guidance and mentorship to junior team members and peers.
• Focus on business practicality and the 80/20 rule; very high bar for output quality, but recognize the business benefit of "having something now" vs "perfection sometime in the future".

What does SUCCESS look like?
Success in this role means delivering AI-driven solutions that improve efficiency, accelerate revenue growth, and establish us as an innovator in applied AI. You’ll be recognized for shipping high-quality models into production, fostering a culture of experimentation, and mentoring the next generation of ML talent.

The MUST Haves: 

• Bachelor's degree or higher in Computer Science, Engineering, or a related field.
• Five or more (5+) years of experience in software development/engineering focused on machine learning.
• Expertise in Python, writing production-quality code. Expertise in SQL for big data exploratory analysis and feature engineering. 
• Two or more (2+) years of experience working in cloud data environments (e.g. GCP, AWS, Databricks).
• Excellent understanding of machine learning techniques and algorithms, such as DNN, Boosting Trees, Random Forests, etc.