Position Summary:

Are you an AI/ML Engineer who loves to build and implement innovative solutions that create value at scale? If so, you might be the perfect fit for our AI/ML Engineer role at our company.

In this role, you will work with data scientists, engineers, and stakeholders to design, deploy, and operationalize state-of-the-art AI/ML systems that solve complex business problems. You will also drive the innovation of MLOps platforms and processes for the full machine learning lifecycle—from model experimentation, to CI/CD pipelines, to model monitoring and retraining in production environments. You will leverage cloud AI/ML platforms, containerization, automation tools, and processes to streamline AI/ML workflows.

Additionally, you will optimize AI/ML solutions for performance, scalability, and cost. You will serve models via microservices, APIs, and batch scoring pipelines integrated with data products and business applications.

You should have strong expertise in AI/ML platform engineering, modern data platforms, model deployment pipelines, relevant cloud platforms, and programming languages like Python. You should also have excellent problem-solving abilities, attention to detail, and communication skills.

If you are passionate about pushing the boundaries of artificial intelligence and making an impact by delivering innovative ML solutions, this is the role for you. Join us and help shape the future of AI-driven products and services.

Responsibilities:

• Collaborate with stakeholders and data scientists to translate business problems and requirements into ML solutions.
• Engineer end-to-end AI/ML systems from prototyping to production deployment.
• Design and implement AI/ML pipelines for data ingestion, transformation, model training, evaluation, and inference.
• Choose and apply suitable ML algorithms and frameworks such as TensorFlow, PyTorch, and Keras for model development.
• Optimize model performance, accuracy, and fairness using techniques like hyperparameter tuning, error analysis, and model governance.
• Deploy and serve models using REST APIs, serverless functions, or microservices.
• Monitor and maintain AI/ML solutions using AI/MLOps best practices and tools.
• Enhance model scalability, performance, and cost efficiency using cloud AI/ML platforms, containerization, and automation.
• Build AI/MLOps discipline and practice.

Qualifications:

Education & Certificates:

• Bachelor’s degree in Computer Science, Information Technology, or related field.
• Industry Cloud and AI/ML Engineering level certifications desired.

Professional Experience:

• 5+ years of direct experience in AI/ML engineering projects.
• Experience with LLM refinement and vector database embeddings.
• Experience with training, evaluating, and deploying deep learning models.

Competencies & Attributes:

• Proficiency with common ML and data platforms such as AzureML, Amazon SageMaker, Databricks, and Snowflake.
• Knowledge of AI/ML pipelines, AI/MLOps concepts, and tools.
• Ability to build production-grade AI/ML solutions with scalability in mind.
• Experience with MLOps tools and techniques to optimize ML lifecycle management.
• Experience with ML metadata and artifact tracking platforms such as MLflow.
• Experience containerizing and deploying models and solutions to cloud platforms like Azure or AWS.
• Understanding of model governance concepts such as model risk analysis, QA, and compliance.
• Experience with building ML technical architecture diagrams encompassing data, model building, and operations.
• Experience with operating end-to-end ML platforms supporting analytics and ML teams.
• Experience with assessing model technical debt, maintaining pipelines, and keeping systems up-to-date.
• Experience with Python for analytics and ML applications.
• Proficiency with common Python data analysis libraries like NumPy, Pandas, SciPy.
• Experience with common Python ML libraries like Scikit-Learn, TensorFlow, and PyTorch.
• Experience with Jupyter Notebooks for ML experimentation and prototyping.
• Ability to transition ML prototypes to production solutions.
• Experience with Terraform for IaC of ML infrastructure on Azure, AWS cloud platforms.
• Strong problem solving, analytical, and communication skills.

Benefits/Compensation:

The compensation range for this role is specific to Washington, D.C., and takes into account a wide range of factors including but not limited to the skill sets required/preferred; prior experience and training; licenses and/or certifications.

The anticipated base salary range for this role is $170,000 to $190,000.

In addition to the base salary, the hired professional will enjoy a comprehensive benefits package spanning retirement benefits, health insurance, life insurance and disability, paid time off, paid holidays, family planning benefits, and various wellness programs. Additionally, the hired professional may also be eligible to participate in an annual discretionary incentive program, the award of which will be dependent on various factors, including, without limitation, individual and organizational performance.

Due to the high volume of candidates, please be advised that only candidates selected to interview will be contacted.

Company Information:

Our company is a global investment firm with significant assets under management and a diverse portfolio. We emphasize development, retention, and inclusion through our internal processes and various Employee Resource Groups (ERGs). Our purpose is to invest wisely and create value on behalf of our investors, which include public and private pension funds, wealthy individuals and families, sovereign wealth funds, unions, and corporations. We invest across multiple segments and have expertise in various industries, including aerospace, defense, government services, consumer and retail, energy, financial services, healthcare, industrial, real estate, technology and business services, telecommunications and media, and transportation.

We believe that diverse teams perform better, so we seek to create a community where we continually exchange insights, embrace different perspectives, and leverage diversity as a competitive advantage. This is why we are committed to growing and cultivating teams that include people with a variety of perspectives, providing unique lenses through which to view potential deals, support, and run our business.

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