Senior Engineer-AI/ML
Job
TEKsystems
Remote
$149,800 Salary, Full-Time
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Job Description
Think of TEKsystems Global Services (TGS) as the growth solution for enterprises today. We unleash growth through technology, strategy, design, execution and operations with a customer-first mindset for bold business leaders. We deliver cloud, data and customer experience solutions. Our partnerships with leading cloud, design and business intelligence platforms fuel our expertise. We value deep relationships, dedication to serving others and inclusion. We drive positive outcomes for our people and our business, and we stay true to our commitments and act in harmony with our words. We exist to create significant opportunity for people to achieve fulfillment through career success. Ready to join us? Here's what the opportunity supported through our TGS Talent Acquisition Team requires: We are seeking a highly skilled and motivated Senior AI/ML Engineer with 5-7 years of experience in data engineering and at least 3 years in AI/ML engineering. The ideal candidate will have hands-on expertise in designing, developing, and deploying secure, scalable, and high-performance ML pipelines ensuring full compliance with industry standard security and risk framework like
RMF / NIST / CMMC
frameworks. The ideal candidate should have proficiency in Amazon Web Service (AWS) and/or Google Cloud Platform (GCP) with a solid foundation in data engineering, Machine Learning and MLOps cloud-native tools, and data governance. The ideal candidate should be a team player, responsible for the development and orchestration of AI/ML components of various solutions delivered by Data & A/I Practice for our clients. Essential Functions- Actively involves in requirement gathering workshops from customers, translating the functional requirements into technical solutions, and translating complex technical concepts into actionable insights for stakeholders
- Actively participates in architectural discussions independently or under guidance / supervision from Practice Architect and/or Lead Engineer to design and develop effective, efficient, reliable, secure, and scalable data engineering solutions as per the overall data management strategy
- Builds end-to-end machine learning pipelines using AWS (e.g., SageMaker, Lambda, S3) or GCP (e.g., Vertex AI, Cloud Functions, BigQuery) for training, evaluation, and model lifecycle management and ensure scalability, reliability, and performance of ML models in production environments
- Build, train, and fine-tune models using frameworks like TensorFlow, PyTorch, or Scikit-learn and apply techniques such as hyperparameter tuning, feature engineering, and model evaluation to continuously improve accuracy and efficiency.
- Design and implement robust data ingestion, transformation, and storage solutions using cloud-native tools (e.g., AWS Glue, GCP Dataflow) while ensuring data quality, governance, and compliance following industry and/or organizational standards.
- Develop and maintain CI/CD pipelines for ML workflows using tools like AWS CodePipeline or GCP Cloud Build automating model deployment, monitoring, and rollback strategies to support continuous delivery.
- Implement IAM roles, VPC configurations, and encryption protocols to safeguard data and models following best practices for cost optimization and cloud security.
- Collaborate with data scientists, DevSecOps engineers, and cybersecurity SMEs to ensure secure data processing, model deployment and operationalize the deployed models.
- Create prototypes and evaluate emerging tools and methodologies to drive innovation within the team.
- Occasional support to Sales and Pre-Sales partners to convert opportunity to revenue through thought leadership in the designated area of expertise (AI/ML)
Mandatory Skills/Competencies:
- Bachelor or master degree in Computer Science, Data Science, Engineering, or related field.
- 5-7 years of hands-on experience in data engineering (preferably in cloud environment) with 3+ years of experience in Machine Learning engineering roles, preferably in secure or classified environments
- Strong proficiency in Python, PySpark, SQL, Jupyter notebooks, and distributed computing and optionally R, Java, or Scala
- Strong understanding of core machine learning, deep learning, and NLP
- Deep understanding of cloud-native ML services like Amazon SageMaker, AWS Lambda, GCP Vertex AI, and BigQuery ML.
- Proficiency in supervised, unsupervised, and deep learning techniques.
- Hands-on experience with TensorFlow, PyTorch, Scikit-learn, or similar libraries
- Knowledge of CI/CD pipelines, model versioning, and automated deployment and experience with tools like Kubeflow, MLflow, Docker, and Kubernetes.
- Production level experience in dealing with structured, semi-structured and unstructured data from APIs, RDBMS, and/or streaming sources into data lakes, or storages e.g., Snowflake, S3, Google Cloud Storage (GCS) etc.
- Ability to design robust evaluation metrics and monitor model performance post-deployment and experience with drift detection, retraining strategies, and alerting mechanisms.
- Solid understanding of data privacy, IAM roles, encryption, and compliance standards (e.g., GDPR, HIPAA) and ability to apply the knowledge to implement secure ML solutions in cloud environments.
- Strong analytical skills to translate business problems into ML solutions, troubleshoot complex issues across data, model, and infrastructure layers.
- Excellent verbal and written communication skills.
- Ability to work cross-functionally with product managers, data scientists, and engineering teams.
- Passion for staying updated with the latest in AI/ML research and cloud technologies and ability to evaluate and adopt emerging tools and methodologies.
Preferred Qualifications:
- Familiarity with DoD data strategy, RMF / NIST / CMMC / FedRAMP frameworks
- Experience with Generative AI, LLMs, transformer architecture, and prompt engineering
- Knowledge of Agentic AI frameworks
- Industry recognized associate or advanced level AI/ML certification from
AWS/ GCP
/ Snowflake / Databricks Certification such as: AWS Machine Learning Engineer- Associate AWS Machine Learning
- Specialty GCP
- Professional Machine Learning Engineer Databricks Certified Machine Learning Associate Databricks Certified Machine Learning Professional Job Type & Location This is a Permanent position based out of Baltimore, MD. Pay and Benefits The pay range for this position is $119800.00
- $179800.00/yr. We reserve the right to pay above or below the posted wage based on factors unrelated to sex, race, or any other protected classification. Additional earnings may be available through incentive programs like annual bonuses, profit sharing, etc. Our full-time, internal employment benefits include the following:
- Medical, Dental, and Vision
- Critical Illness, Accident, and Hospital
- 401(k) Retirement Plan
- Pre-tax and Roth post-tax contributions available
- Life Insurance (Voluntary Life and AD&D for employee and dependents)
- Short and Long-Term Disability
- Health Spending Account (HSA)
- Transportation Benefits
- Employee Assistance Program
- Time Off/Leave (PTO, Vacation or Sick Leave) Workplace Type This is a fully remote position.
San Francisco Fair Chance Ordinance:
Pursuant to the San Francisco Fair Chance Ordinance, for all positions located in the city and county of San Francisco, we will consider for employment qualified applicants with arrest and conviction records.Massachusetts Lie Detector:
It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability. Use of Artificial Intelligence (AI): We may use Artificial Intelligence (AI) to support parts of our hiring process, including sourcing, screening, and evaluating candidates. AI helps assess applications and qualifications, but final decisions are made by our hiring team. By applying, you acknowledge and agree that your application may be reviewed using AI tools.Similar remote jobs
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