Senior AI/ML Engineer
Company: Avature
Location: Washington
Posted on: May 18, 2024
Job Description:
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 Senior AI/ML engineer role at Carlyle.
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 at Carlyle.
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, 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 practiceQualifications 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
- 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 model risk
analysis, QA, compliance
- Experience with building ML technical architecture diagrams
encompassing data, model building, operations
- Experience with operating end-to-end ML platforms supporting
analytics and ML teams
- Experience with assessing model technical debt, maintaining
pipelines, 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, 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 Due
to the high volume of candidates, please be advised that only
candidates selected to interview will be contacted by The Carlyle
Group. Company Information The Carlyle Group (NASDAQ: CG) is a
global investment firm with $425 billion of assets under management
and more than half of the AUM managed by women, across 595
investment vehicles as of March 31, 2024. Founded in 1987 in
Washington, DC, Carlyle has grown into one of the world's largest
and most successful investment firms, with more than 2,200
professionals operating in 28 offices in North America, Europe, the
Middle East, Asia and Australia. Carlyle places an emphasis on
development, retention and inclusion as supported by our internal
processes and seven Employee Resource Groups (ERGs). Carlyle's
purpose is to invest wisely and create value on behalf of its
investors, which range from public and private pension funds to
wealthy individuals and families to sovereign wealth funds, unions
and corporations. Carlyle invests across three segments - Global
Private Equity, Global Credit and Investment Solutions - and has
expertise in various industries, including: aerospace, defense &
government services, consumer & retail, energy, financial services,
healthcare, industrial, real estate, technology & business
services, telecommunications & media and transportation. At
Carlyle, we know 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. That is why we are committed to growing and cultivating
teams that include people with a variety of perspectives, people
who provide unique lenses through which to view potential deals,
support and run our business.
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Keywords: Avature, Bel Air North , Senior AI/ML Engineer, Engineering , Washington, Maryland
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