### Job_Dedcrip:
Job Description.Role: Lead Machine Learning EngineerLocation: Jersey City, NJ/Durham, NC/Merrimack, NH/Westlake, TX/Boston, MA(Any Client location) (Hybrid, 1 Week onsite/Month)Duration: 9+ MonthsPay rate starts from: $80/Hr on W2 W2 OnlyMust Haves:.10+ year of programming (3+ years in Python – people who can write in Python) / Fast API or Flask2+ years of AWS experience in the Engineering space (need to know the Ecosystem).The Expertise You Have.Has Bachelor’s or Master’s Degree in a technology related field (e.g. Engineering, Computer Science, etc.).8+ years of proven experience in implementing Big data solutions in data analytics space.2+ years of experience in developing ML infrastructure and MLOps in the Cloud using AWS Sagemaker.Extensive experience working with machine learning models with respect to deployment, inference, tuning, and measurement required.Experience in Object Oriented Programming (Java, Scala, Python), SQL, Unix scripting or related programming languages and exposure to some of Python’s ML ecosystem (numpy, panda, sklearn, tensorflow, etc.).Experience with building data pipelines in getting the data required to build and evaluate ML models, using tools like Apache Spark or other distributed data processing frameworks.Data movement technologies (ETL/ELT), Messaging/Streaming Technologies (AWS SQS, Kinesis/Kafka), Relational and NoSQL databases (DynamoDB, EKS, Graph database), API and in-memory technologies.Strong knowledge of developing highly scalable distributed systems using Open-source technologies.Experience with CI/CD tools (e.g., Jenkins or equivalent), version control (Git), orchestration/DAGs tools (AWS Step Functions, Airflow, Luigi, Kubeflow, or equivalent).Solid experience in Agile methodologies (Kanban and SCRUM)..The Skills You Bring.You have strong technical design and analysis skills.You the ability to deal with ambiguity and work in fast paced environment.Your experience supporting critical applications.You are familiar with applied data science methods, feature engineering and machine learning algorithms.Your Data wrangling experience with structured, semi-structure and unstructured data.Your experience building ML infrastructure, with an eye towards software engineering.You have excellent communication skills, both through written and verbal channels.You have excellent collaboration skills to work with multiple teams in the organization.Your ability to understand and adapt to changing business priorities and technology advancements in Big data and Data Science ecosystem..The Value You Deliver.Designing & developing a feature generation & store framework that promotes sharing of data/features among different ML models.Partner with Data Scientists and to help use the foundational platform upon which models can be built and trained.Operationalize ML Models at scale (e.g. Serve predictions on tens of millions of customers).Build tools to help detect shifts in data/features used by ML models to help identify issues in advance of deteriorating prediction quality, monitoring the uncertainty of model outputs, automating prediction explanation for model diagnostics.Exploring new technology trends and using them to simplify our data and ML ecosystem.Driving Innovation and implementing solutions with future thinking.Guiding teams to improve development agility and productivity.Resolving technical roadblocks and mitigating potential risks.Delivering system automation by setting up continuous integration/continuous delivery pipelines..About Us Below is the brief introduction of SPECTRAFORCE, the benefits we offer and the disclaimers:Established in 2004, SPECTRAFORCE is one of the largest and fastest-growing diversity-owned staffing firms in the US. The growth of our company is a direct result of our global client service delivery model that is powered by our state-of-the-art A.I. proprietary talent acquisition platform, robust ISO 9001:2015/ISO 27001 certified processes, and strong and passionate client engaged teams.We have built our business by providing talent and project-based solutions, including Contingent, Permanent, and Statement of Work (SOW) services to over 130 clients in the US, Canada, Puerto Rico, Costa Rica, and India. Key industries that we service include Technology, Financial Services, Life Sciences, Healthcare, Telecom, Retail, Utilities and Transportation.SPECTRAFORCE is built on a concept of “human connection,” defined by our branding attitude of NEWJOBPHORIA®, which is the excitement of bringing joy and freedom to the work lifestyle so our people (and clients) can reach their highest potential. Our entire workflow and teams are trained to cultivate the joy of NEWJOBPHORIA® with candidates and employees throughout their engagement with SPECTRAFORCE. http://www.spectraforce.com Benefits: SPECTRAFORCE offers ACA compliant health benefits as well as dental, vision, accident, and hospital indemnity insurances. Additional benefits SPECTRAFORCE offers to the eligible employees include commuter benefits, 401K plan with matching and a referral bonus program. SPECTRAFORCE offers unpaid leave as well as paid sick leave when required by law.Equal Opportunity Employer: SPECTRAFORCE is an equal opportunity employer and does not discriminate against any employee or applicant for employment because of race, religion, color, sex, national origin, age, sexual orientation, gender identity, genetic information, disability or veteran status, or any other category protected by applicable federal, state, or local laws. Please contact Human Resources at nahr@spectraforce.com if you require reasonable accommodation

### Response:

Must Haves:- 10 year of programming (3 years in Python people who can write in Python) / Fast API or Flask- 2 years of AWS experience in the Engineering space (need to know the Ecosystem).The Expertise You Have:- Has Bachelors or Masters Degree in a technology related field (e.g. Engineering, Computer Science, etc.).- 8 years of proven experience in implementing Big data solutions in data analytics space.- 2 years of experience in developing ML infrastructure and MLOps in the Cloud using AWS Sagemaker.- Extensive experience working with machine learning models with respect to deployment, inference, tuning, and measurement required.- Experience in Object Oriented Programming (Java, Scala, Python), SQL, Unix scripting or related programming languages and exposure to some of Pythons ML ecosystem (numpy, panda, sklearn, tensorflow, etc.).- Experience with building data pipelines in getting the data required to build and evaluate ML models, using tools like Apache Spark or other distributed data processing frameworks.- Data movement technologies (ETL/ELT), Messaging/Streaming Technologies (AWS SQS, Kinesis/Kafka), Relational and NoSQL databases (DynamoDB, EKS, Graph database), API and in-memory technologies.- Strong knowledge of developing highly scalable distributed systems using Open-source technologies.- Experience with CI/CD tools (e.g., Jenkins or equivalent), version control (Git), orchestration/DAGs tools (AWS Step Functions, Airflow, Luigi, Kubeflow, or equivalent).- Solid experience in Agile methodologies (Kanban and SCRUM).The Skills You Bring:- You have strong technical design and analysis skills.- You the ability to deal with ambiguity and work in fast paced environment.- Your experience supporting critical applications.- You are familiar with applied data science methods, feature engineering and machine learning algorithms.- Your Data wrangling experience with structured, semi-structure and unstructured data.- Your experience building ML infrastructure, with an eye towards software engineering.- You have excellent communication skills, both through written and verbal channels.- You have excellent collaboration skills to work with multiple teams in the organization.- Your ability to understand and adapt to changing business priorities and technology advancements in Big data and Data Science ecosystem.